Senior Data Engineer-100%Remote

We are seeking a highly skilled Senior Data Engineer to help evaluate and design robust data
integration solutions for large-scale, disparate datasets spanning multiple platforms and
infrastructure types, including cloud-based and potentially undefined or evolving environments.
This role is critical in identifying optimal data ingestion, normalization, and transformation
strategies while collaborating with cross-functional teams to ensure data accessibility, reliability,
and security across systems.

Responsibilities:
Responsible for developing, expanding and optimizing our data and data pipeline
architecture, as well as optimizing data flow and collection for cross functional teams.
Support software developers, database architects, data analysts and data scientists on
data initiatives and ensure optimal data delivery architecture is consistent throughout
ongoing projects.
Creates new pipeline and maintains existing pipeline, updates Extract, Transform, Load
(ETL) process, creates new ETL feature , builds PoCs with Redshift Spectrum,
Databricks, AWS EMR, SageMaker, etc.;
Implements, with support of project data specialists, large dataset engineering: data
augmentation, data quality analysis, data analytics (anomalies and trends), data
profiling, data algorithms, and (measure/develop) data maturity models and develop data
strategy recommendations.
Operate large-scale data processing pipelines and resolve business and technical
issues pertaining to the processing and data quality.
Assemble large, complex sets of data that meet non-functional and functional business
requirements
Identify, design, and implement internal process improvements including re-designing
data infrastructure for greater scalability, optimizing data delivery, and automating
manual processes ?
Building required infrastructure for optimal extraction, transformation and loading of data
from various data sources using AWS and SQL technologies
Building analytical tools to utilize the data pipeline, providing actionable insight into key
business performance metrics including operational efficiency and customer acquisition?
Working with stakeholders including data, design, product and government stakeholders
and assisting them with data-related technical issues
Write unit and integration tests for all data processing code.
Work with DevOps engineers on CI, CD, and IaC.

Read specs and translate them into code and design documents.
Perform code reviews and develop processes for improving code quality.
Perform other duties as assigned.
Requirements
All candidates must pass public trust clearance through the U.S. Federal Government. This
requires candidates to either be U.S. citizens or pass clearance through the Foreign National
Government System which will require that candidates have lived within the United States for at
least 3 out of the previous 5 years, have a valid and non-expired passport from their country of
birth and appropriate VISA/work permit documentation.

Bachelor's degree in Computer Science, Software Engineering, Data Science, Statistics,
or related technical field.
10+ years of experience in software/data engineering, including data pipelines, data
modeling, data integration, and data management.
Expertise in data lakes, data warehouses, data meshes, data modeling and data
schemas (star, snowflake ).
Strong expertise in SQL, Python, and/or R, with applied experience in Apache Spark and
large-scale processing using PySpark or Sparklyr.
Experience with Databricks in a production environment.
Strong experience with AWS cloud-native data services, including S3, Glue, Athena, and
Lambda.
Strong proficiency with GitHub and GitHub Actions, including test-driven development.
Proven ability to work with incomplete or ambiguous data infrastructure and design
integration strategies.
Excellent analytical, organizational, and problem-solving skills.
Strong communication skills, with the ability to translate complex concepts across
technical and business teams.
Proven experience working with petabyte-level data systems.

Preferred Qualifications:

Experience working with healthcare data, especially CMS (Centers for Medicare &
Medicaid Services) datasets.

CMS and Healthcare Expertise: In-depth knowledge of CMS regulations and experience
with complex healthcare projects; in particular, data infrastructure related projects or
similar.
Demonstrated success providing support within the CMS OIT environment, ensuring
alignment with organizational goals and technical standards.
Demonstrated experience and familiarity with CMS OIT data systems (e.g. IDR-C, CCW,
EDM, etc.)
Experience with cloud platform services: AWS and Azure.
Experience with streaming data (Kafka, Kinesis, Pub/Sub).
Familiarity with data governance, metadata management, and data quality practices.