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Infinitive

Data Engineer

Infinitive, Mc Lean, Virginia, us, 22107

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Data Engineer

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Infinitive

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 8 times, most recently in 2025. 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 skilled Data Engineer to join our team and play a key role in designing, building, and maintaining robust data pipelines and platforms. The ideal candidate will have strong experience with Python, AWS (Glue, S3, Lambda, CloudWatch), Databricks, Apache Spark, SQL, Snowflake, and DynamoDB. This role involves working with large-scale data processing systems, optimizing ETL/ELT workflows, and ensuring the reliability, scalability, and security of data solutions.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines using AWS Glue, Databricks, and Apache Spark

Work with structured and semi-structured data in Snowflake, DynamoDB, and S3

Optimize and troubleshoot Spark jobs for performance and cost efficiency

Develop and maintain Lambda functions to support real-time and batch data processing

Implement data quality, validation, and monitoring using CloudWatch and other observability tools

Design and optimize complex SQL queries for data transformation, aggregation, and reporting

Collaborate with cross-functional teams, including Data Scientists, Analysts, and DevOps teams, to support data-driven decision-making

Implement best practices for data security, governance, and compliance in the cloud environment

Automate data workflows and CI/CD pipelines using infrastructure-as-code and Git-based version control

Required Qualifications

3+ years of experience in Data Engineering or a similar role

Strong proficiency in Python for data processing and automation

Hands-on experience with AWS services including Glue, S3, Lambda, CloudWatch, DynamoDB

Expertise in Databricks and Apache Spark for large-scale data processing

Proficient in SQL for querying and manipulating structured data

Experience working with Snowflake, including schema design and performance tuning

Knowledge of data lake and data warehouse architectures

Familiarity with data security, IAM roles, and cloud-based authentication mechanisms

Strong problem-solving and debugging skills in a cloud-based data environment

Preferred Qualifications

Experience with streaming data architectures using Kafka, Kinesis, or Pub/Sub

Knowledge of orchestration tools such as Airflow, Step Functions, or MWAA

Experience with Terraform or CloudFormation for infrastructure automation

Understanding of data governance frameworks (e.g. Dataplex, Alation, or Unity Catalog)

Experience in CI/CD and DevOps practices for data engineering pipelines

Hands-on experience with monitoring and logging tools, including Splunk and NewRelic

Seniority level Mid-Senior level

Employment type Full-time

Job function Sales, General Business, and Education

Industries Wireless Services, Telecommunications, and Communications Equipment Manufacturing

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