Lead Data Engineer

Capital Technology Group provides expert consulting services software development, digital transformation, human-centered design, data analytics and visualization, and cybersecurity.

Our multidisciplinary teams use agile methodologies to rapidly and incrementally deliver value in close collaboration with our clients. For over a decade, we have been trusted by both federal and commercial clients to solve complex, mission-critical business challenges. The quality of our work has been recognized by our partners and peers through our inclusion in the Digital Services Coalition, a group of forward- thinking firms recognized for excellence in delivering IT services. 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), dbt, SQL (PostgreSQL), and AWS Glue

. Develop and optimize

AWS-native

data platforms leveraging

AWS Glue, Amazon EMR, Amazon MWAA (Apache Airflow), Lambda, Step Functions, Amazon S3, Redshift, RDS, DMS, and CloudWatch

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

Apache Iceberg, Parquet, ORC, and Avro

. Design and optimize analytical data platforms using

Amazon Athena, Trino, Hive, OpenSearch, and enterprise data catalog technologies

. Integrate enterprise and external data sources across relational and NoSQL platforms including

PostgreSQL, Oracle, Redshift, GraphDB, and other NoSQL databases

. 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

,

Harness

, and enterprise

CI/CD

pipelines while leveraging

SNS

,

SQS

, and

EventBridge

for event-driven architectures. 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. Lead modernization initiatives migrating legacy platforms including

IBM DataStage

,

Hadoop

,

Rundeck

, and shell-based workflows to cloud-native AWS services. 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 15+ years of professional experience in data engineering, data architecture, or related fields Strong hands-on experience with: Apache Spark (PySpark) required

,

Python

,

SQL (PostgreSQL)

, and

dbt

for large-scale data engineering, ETL/ELT development, data transformation, and data modeling. AWS Glue

,

Amazon EMR

,

Amazon MWAA (Apache Airflow)

,

AWS Lambda

,

AWS Step Functions

,

Amazon S3

,

Amazon Redshift

,

Amazon RDS

,

AWS DMS

, and

Amazon CloudWatch

. 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

,

ORC

, and

Avro

. Designing and optimizing solutions using relational and NoSQL databases including

PostgreSQL

,

Redshift

,

Oracle

,

GraphDB

, and other

NoSQL

platforms. Building reliable, high-performance data platforms through

performance tuning

,

system optimization

, and enterprise-scale

ETL/ELT

architectures. Java

development and modern

CI/CD

practices using

Harness

.

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. Full Time Employee Benefits

Remote Work

(Hybrid roles will be specified in the job post) Competitive Compensation Package Medical, Dental, and Vision Life Insurance, Short/Long Term Disability Employee Assistance Program 401(k) with 4% matching Liberal PTO vacation policy Generous Annual Continuing Education Annual Wellness Budget Bonus Incentive Programs

(Employee referrals and performance-based rewards) Thanks for your interest in Capital Technology Group! Capital Technology Group is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law.