Infinitive Inc
McLean, Virginia
Job DescriptionJob Description About Infinitive Infinitive is a data and AI consultancy that helps clients modernize, monetize, and operationalize their data to generate lasting value. They pride themselves on their deep industry and technology expertise, ensuring that they drive and sustain the adoption of new capabilities. Infinitive is committed to aligning their team with their clients' culture, ensuring a successful partnership by bringing the right mix of talent and skills for high return on investment. Infinitive has earned recognition as one of the "Best Small Firms to Work For" by Consulting Magazine, receiving this accolade nine times, most recently in 2026. They have also been honored as a "Top Workplace" by the Washington Post, "Best Places to Work" by the Washington Business Journal, and "Best Places to Work" by Virginia Business. Job Summary We are seeking a Technical Program Manager (TPM) with a strong foundation in AWS or Databricks data platforms, large-scale ETL integrations, and enterprise client engagement. This role requires an individual capable of bridging engineering, product, and external stakeholders-driving technical architecture decisions, managing the delivery of complex data modernization programs, and leading deep-dive data attribute discovery. The ideal candidate is a proactive leader who excels in program governance, customer-facing technical alignment, and large-scale data mapping. Key Responsibilities Client Engagement & Roadmap Alignment: Play a central, customer-facing role partnering with clients; translate their business needs and timelines into strategic program roadmaps. Batch Data & Attribute Discovery: Lead technical discussions around batch data requirements, rigorously documenting and verifying business justifications for 1,000s of data attributes across legacy and target modern schemas. Architectural Partnership: Collaborate with engineering leads to shape technical architecture across AWS platforms, including Glue, Lambda, Aurora, S3, EMR, and DynamoDB. Program Execution: Lead the end-to-end delivery of scalable ETL pipelines and data integration strategies to support legacy-to-modern system transitions. Governance & Alignment: Own program plans, cross-team alignment, risk mitigation, and executive reporting across internal and external stakeholders. Cross-Functional Collaboration: Serve as a strategic liaison between clients, engineering, and product to ensure architectural decisions align directly with business outcomes. TPM Enablement: Build frameworks, documentation, and onboarding paths to support incoming TPMs and scale operational excellence. Required Skills & Experience 7+ years of experience in technical program management, client-facing solutions architecture, or engineering leadership. Proven experience managing large-scale data discovery, mapping, and business justification workflows for 1,000s of data attributes across complex legacy client bases. Demonstrated ability to serve in a high-impact customer-facing capacity, aligning multi-client needs to platform roadmaps. Strong technical knowledge of AWS data services, including Glue, Lambda, Aurora, EMR, DynamoDB, and S3. Hands-on experience with ETL processes, batch processing, Spark/PySpark, and enterprise data migration initiatives. Familiarity with distributed systems, CI/CD pipelines, and container orchestration using Docker and Kubernetes. Proven track record in executive stakeholder engagement, strategic roadmap planning, and end-to-end program delivery. Nice-to-Have Qualifications Experience with mainframe and legacy batch system migrations (e.g., COBOL-based systems, flat files, fixed-width feeds). Background in platform modernization, ERP systems, or financial technology environments. Demonstrated ability to contribute to the onboarding, training, and scaling of TPM teams. Infinitive is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $90,000 - $154,00.00. Infinitive is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. Powered by JazzHR KaK6PBYDDT
Job DescriptionJob Description About Infinitive Infinitive is a data and AI consultancy that helps clients modernize, monetize, and operationalize their data to generate lasting value. They pride themselves on their deep industry and technology expertise, ensuring that they drive and sustain the adoption of new capabilities. Infinitive is committed to aligning their team with their clients' culture, ensuring a successful partnership by bringing the right mix of talent and skills for high return on investment. Infinitive has earned recognition as one of the "Best Small Firms to Work For" by Consulting Magazine, receiving this accolade nine times, most recently in 2026. They have also been honored as a "Top Workplace" by the Washington Post, "Best Places to Work" by the Washington Business Journal, and "Best Places to Work" by Virginia Business. Job Summary We are seeking a Technical Program Manager (TPM) with a strong foundation in AWS or Databricks data platforms, large-scale ETL integrations, and enterprise client engagement. This role requires an individual capable of bridging engineering, product, and external stakeholders-driving technical architecture decisions, managing the delivery of complex data modernization programs, and leading deep-dive data attribute discovery. The ideal candidate is a proactive leader who excels in program governance, customer-facing technical alignment, and large-scale data mapping. Key Responsibilities Client Engagement & Roadmap Alignment: Play a central, customer-facing role partnering with clients; translate their business needs and timelines into strategic program roadmaps. Batch Data & Attribute Discovery: Lead technical discussions around batch data requirements, rigorously documenting and verifying business justifications for 1,000s of data attributes across legacy and target modern schemas. Architectural Partnership: Collaborate with engineering leads to shape technical architecture across AWS platforms, including Glue, Lambda, Aurora, S3, EMR, and DynamoDB. Program Execution: Lead the end-to-end delivery of scalable ETL pipelines and data integration strategies to support legacy-to-modern system transitions. Governance & Alignment: Own program plans, cross-team alignment, risk mitigation, and executive reporting across internal and external stakeholders. Cross-Functional Collaboration: Serve as a strategic liaison between clients, engineering, and product to ensure architectural decisions align directly with business outcomes. TPM Enablement: Build frameworks, documentation, and onboarding paths to support incoming TPMs and scale operational excellence. Required Skills & Experience 7+ years of experience in technical program management, client-facing solutions architecture, or engineering leadership. Proven experience managing large-scale data discovery, mapping, and business justification workflows for 1,000s of data attributes across complex legacy client bases. Demonstrated ability to serve in a high-impact customer-facing capacity, aligning multi-client needs to platform roadmaps. Strong technical knowledge of AWS data services, including Glue, Lambda, Aurora, EMR, DynamoDB, and S3. Hands-on experience with ETL processes, batch processing, Spark/PySpark, and enterprise data migration initiatives. Familiarity with distributed systems, CI/CD pipelines, and container orchestration using Docker and Kubernetes. Proven track record in executive stakeholder engagement, strategic roadmap planning, and end-to-end program delivery. Nice-to-Have Qualifications Experience with mainframe and legacy batch system migrations (e.g., COBOL-based systems, flat files, fixed-width feeds). Background in platform modernization, ERP systems, or financial technology environments. Demonstrated ability to contribute to the onboarding, training, and scaling of TPM teams. Infinitive is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $90,000 - $154,00.00. Infinitive is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. Powered by JazzHR KaK6PBYDDT
Infinitive Inc
McLean, Virginia
About Infinitive Infinitive is a data and AI consultancy that helps clients modernize, monetize, and operationalize their data to generate lasting value. They pride themselves on their deep industry and technology expertise, ensuring that they drive and sustain the adoption of new capabilities. Infinitive is committed to aligning their team with their clients' culture, ensuring a successful partnership by bringing the right mix of talent and skills for high return on investment. Infinitive has earned recognition as one of the "Best Small Firms to Work For" by Consulting Magazine, receiving this accolade nine times, most recently in 2026. They have also been honored as a "Top Workplace" by the Washington Post, "Best Places to Work" by the Washington Business Journal, and "Best Places to Work" by Virginia Business. About the Role We are seeking an experienced Data Engineer to help design, build, and scale our next-generation event-driven data platforms. In this role, you will be instrumental in bridging high-throughput distributed streaming with complex, fault-tolerant workflow orchestration and strict data governance. You will work extensively with Apache Kafka for real-time event streaming and Temporal (the open-source, durable execution engine originating from Uber/Cadence) to build resilient, distributed stateful workflows and data pipelines. A core focus of this position is establishing robust data schema design and automated validation to ensure strong data contracts across distributed systems. Alongside these technologies, you will design robust batch and streaming ETL/ELT pipelines leveraging Python, Apache Spark, and modern cloud data warehouses/lakehouses. Key Responsibilities Stream Processing & Messaging: Architect, deploy, and maintain high-volume distributed data streams using Apache Kafka (producers, consumers, Kafka Connect, Schema Registry). Data Schema Design & Validation: Establish and enforce schema design standards, versioning strategies, and automated schema validation (e.g., Avro, Protobuf, JSON Schema) to maintain strict data contracts across microservices, streaming consumers, and lakehouse storage. Resilient Workflow Orchestration: Design and implement durable execution workflows using Temporal to coordinate long-running distributed pipelines, compensate transactions (Saga pattern), and manage cross-system ETL tasks. Pipeline Development: Build end-to-end batch and near-real-time pipelines using Python, SQL, and Apache Spark / PySpark. Data Modeling & Warehousing: Design and optimize analytical data models (dimensional/star schema) in modern cloud data warehouses/lakehouses (e.g., Snowflake, BigQuery, Databricks, Redshift). Reliability & Data Quality: Implement automated testing, continuous schema validation, data drift detection, and observability across streaming and batch workflows. Cross-Functional Collaboration: Partner with software engineers, machine learning engineers, and analysts to define standard schema definitions, data contracts, and production-grade CI/CD release patterns. Required Experience 4+ years of professional experience in data engineering, backend distributed systems, or software engineering. Hands-on experience with Temporal (or Cadence): Proven understanding of durable workflows, activities, retries, signals, queries, and long-running distributed task orchestration. Deep expertise with Apache Kafka: Practical experience with message partitioning, consumer groups, offset management, and topic design. Strong background in Data Schema Design & Validation: Demonstrated proficiency with schema definition frameworks (Apache Avro, Protocol Buffers/gRPC, or JSON Schema). Practical experience managing schema evolution, compatibility modes (backward/forward/full), and schema registries (e.g., Confluent Schema Registry, AWS Glue Schema Registry). Experience enforcing data validation rules, contract testing, and data quality checks (e.g., Great Expectations, Pandera, Pydantic, dbt tests). Strong programming proficiency in Python (Go or Java is a plus) with clean code, design patterns, and unit/integration testing standards. Distributed computing experience: Hands-on development with Apache Spark (PySpark/Spark SQL) processing large-scale datasets. Advanced SQL & Data Modeling: Strong experience with relational databases, dimensional data modeling, and query performance tuning. Infinitive is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $90,000 - $154,00.00. Infinitive is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.
About Infinitive Infinitive is a data and AI consultancy that helps clients modernize, monetize, and operationalize their data to generate lasting value. They pride themselves on their deep industry and technology expertise, ensuring that they drive and sustain the adoption of new capabilities. Infinitive is committed to aligning their team with their clients' culture, ensuring a successful partnership by bringing the right mix of talent and skills for high return on investment. Infinitive has earned recognition as one of the "Best Small Firms to Work For" by Consulting Magazine, receiving this accolade nine times, most recently in 2026. They have also been honored as a "Top Workplace" by the Washington Post, "Best Places to Work" by the Washington Business Journal, and "Best Places to Work" by Virginia Business. About the Role We are seeking an experienced Data Engineer to help design, build, and scale our next-generation event-driven data platforms. In this role, you will be instrumental in bridging high-throughput distributed streaming with complex, fault-tolerant workflow orchestration and strict data governance. You will work extensively with Apache Kafka for real-time event streaming and Temporal (the open-source, durable execution engine originating from Uber/Cadence) to build resilient, distributed stateful workflows and data pipelines. A core focus of this position is establishing robust data schema design and automated validation to ensure strong data contracts across distributed systems. Alongside these technologies, you will design robust batch and streaming ETL/ELT pipelines leveraging Python, Apache Spark, and modern cloud data warehouses/lakehouses. Key Responsibilities Stream Processing & Messaging: Architect, deploy, and maintain high-volume distributed data streams using Apache Kafka (producers, consumers, Kafka Connect, Schema Registry). Data Schema Design & Validation: Establish and enforce schema design standards, versioning strategies, and automated schema validation (e.g., Avro, Protobuf, JSON Schema) to maintain strict data contracts across microservices, streaming consumers, and lakehouse storage. Resilient Workflow Orchestration: Design and implement durable execution workflows using Temporal to coordinate long-running distributed pipelines, compensate transactions (Saga pattern), and manage cross-system ETL tasks. Pipeline Development: Build end-to-end batch and near-real-time pipelines using Python, SQL, and Apache Spark / PySpark. Data Modeling & Warehousing: Design and optimize analytical data models (dimensional/star schema) in modern cloud data warehouses/lakehouses (e.g., Snowflake, BigQuery, Databricks, Redshift). Reliability & Data Quality: Implement automated testing, continuous schema validation, data drift detection, and observability across streaming and batch workflows. Cross-Functional Collaboration: Partner with software engineers, machine learning engineers, and analysts to define standard schema definitions, data contracts, and production-grade CI/CD release patterns. Required Experience 4+ years of professional experience in data engineering, backend distributed systems, or software engineering. Hands-on experience with Temporal (or Cadence): Proven understanding of durable workflows, activities, retries, signals, queries, and long-running distributed task orchestration. Deep expertise with Apache Kafka: Practical experience with message partitioning, consumer groups, offset management, and topic design. Strong background in Data Schema Design & Validation: Demonstrated proficiency with schema definition frameworks (Apache Avro, Protocol Buffers/gRPC, or JSON Schema). Practical experience managing schema evolution, compatibility modes (backward/forward/full), and schema registries (e.g., Confluent Schema Registry, AWS Glue Schema Registry). Experience enforcing data validation rules, contract testing, and data quality checks (e.g., Great Expectations, Pandera, Pydantic, dbt tests). Strong programming proficiency in Python (Go or Java is a plus) with clean code, design patterns, and unit/integration testing standards. Distributed computing experience: Hands-on development with Apache Spark (PySpark/Spark SQL) processing large-scale datasets. Advanced SQL & Data Modeling: Strong experience with relational databases, dimensional data modeling, and query performance tuning. Infinitive is required by law in some jurisdictions to include a reasonable estimate of the compensation range for this role. The determination of this range includes various factors not limited to skill set, level, experience, relevant training, and licensure and certifications. Compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range for this role in the U.S. is $90,000 - $154,00.00. Infinitive is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.