Lead Data Engineer

Client Requirements: applicants MUST BE US Citizens and be able to obtain Public Trust clearance

The CTG Experience

At Capital Technology Group (CTG), our teams are passionate about modernizing how the federal government delivers software. We partner with federal agencies to build secure, scalable, and mission-driven solutions that make a meaningful impact on millions of people. Recognized by The Washington Post as a Top Workplace in 2025 and 2026. CTG fosters a culture rooted in our core values. Our values guide how we work together and support one another, creating an environment where employees feel trusted, empowered, and encouraged to grow both personally and professionally.

About the Role

CTG is seeking a Lead Data Engineer to design, build, and maintain scalable, efficient data pipelines and systems following modern data engineering best practices. The Lead Data Engineer will partner with other Data Engineers to evaluate and prototype new tools and technologies, assess associated risks and benefits, and deliver exceptional value to our clients.

You Will Get To

Design, build, and maintain scalable data pipelines, ETL/ELT workflows, and data models using Python, Apache Spark (PySpark), SQL (PostgreSQL), and AWS Glue.

Develop and optimize AWS-native data platforms leveraging AWS Glue, Amazon EMR, Amazon MWAA (Apache Airflow), Amazon S3, RDS, and CloudWatch.

Build high-performance ingestion, transformation, and orchestration workflows for structured and semi-structured data using Apache Iceberg and Parquet.

Design and optimize analytical data platforms using Amazon Athena, Trino, Hive, OpenSearch, and enterprise data catalog technologies.

Build AI-enabled data solutions using Amazon Bedrock, RAG pipelines, and vector search technologies including Amazon S3 Vectors and OpenSearch vector indexes.

Develop cloud infrastructure using CloudFormation (Infrastructure as Code), GitHub and enterprise CI/CD pipelines.

Improve the reliability, scalability, performance, and maintainability of enterprise data platforms through monitoring, troubleshooting, automation, and continuous optimization.

Support mission-critical analytics and reporting solutions within large-scale AWS-based federal data environments, implementing solutions that comply with FedRAMP and NIST SP 800-53 security controls.

Mentor junior engineers through technical guidance, architecture discussions, and code reviews while promoting engineering best practices.

Collaborate with cross-functional teams in an Agile environment to define requirements, deliver high-quality data solutions, and communicate technical concepts effectively to technical and non-technical stakeholders.

Who You Are

A strategic data engineer who enjoys designing sophisticated systems and solving challenging problems

Strong experience in modern cloud-based solution design

Comfortable balancing business needs with technical constraints and long-term strategy

A strong communicator

Collaborative, proactive, and comfortable navigating ambiguity

Qualifications

Bachelor's degree in Computer Science, Engineering, or a related technical field

8+ years of professional experience in data engineering, data architecture, or related fields

Strong hands-on experience with:

Apache Spark (PySpark) required, Python, SQL, Relational Databases for large-scale data engineering, ETL/ELT development, data transformation, and data modeling.

AWS Glue, Amazon EMR, Amazon MWAA (Apache Airflow), AWS Lambda, Amazon S3, Amazon RDS.

Developing scalable data pipelines, workflow orchestration, and data integration solutions across enterprise environments.

Working with modern data lake technologies and data formats such as Parquet and Iceberg.

Designing and optimizing solutions using relational and NoSQL databases

Building reliable, high-performance data platforms through performance tuning, system optimization, and enterprise-scale ETL/ELT architectures.

Strong analytical and problem-solving skills

Experience working in Agile, iterative software development environments

Ability to quickly learn and apply new technologies and domain knowledge

Excellent written and verbal communication skills, with the ability to explain complex topics to diverse audiences

Nice to Have

Experience supporting analytics, data engineering, or modernization initiatives for financial regulators, capital markets, or other highly regulated environments is a plus.

Experience with Apache Iceberg and modern data lakehouse architectures.

Experience working with unstructured data processing, including document/text processing, embeddings, vector search, and LLM-based data solutions.

Exposure to integrating LLMs and generative AI capabilities into enterprise data pipelines and platforms.

Experience designing data architectures that support both structured and unstructured data at scale.

Salary

We are committed to offering a competitive salary for this position, with an estimated range of $150k to $200k annually. Please note that this range is intended to provide a general idea of what to expect; however, the final offer may vary based on experience, skills, and other factors. The stated range is not a guarantee and is subject to change.