Senior Data Warehouse Engineer

UNAVAILABLE; McLean (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

UNAVAILABLE is seeking a Senior Data Warehouse Engineer to join our team to build, optimize, and scale enterprise data platforms and pipelines in cloud environments. You will work closely with clients to deliver robust data solutions.

The role requires strong problem solving, collaboration with data scientists and engineers, and experience with data modeling, ETL, and governance. You will lead migrations and ensure performance, reliability, and security in a DevSecOps style.

Qualifications

• 5+ years of experience in data engineering, data warehousing, or data architecture.
• Proficiency in Python; also knowledge of Scala, Java, or C++ is a plus.
• Experience designing and implementing data governance strategies.
• Ability to obtain/hold a position of public trust with the US government.

Responsibilities

• Lead and architect the migration of data environments with a focus on performance, reliability, and scalability.
• Design, implement, and optimize data warehouse solutions, ensuring best practices in data modeling, storage, and retrieval.
• Ability to examine and understand complex data pipelines.
• Assess, document, and analyze data sources, ETL workflows, and business intelligence tools.
• Address technical inquiries related to data warehouse customization, integration, and enterprise architecture.
• Develop and maintain robust data pipelines and ETL processes to support business intelligence and analytics.
• Design and enforce data governance strategies, ensuring high data quality and compliance.
• Work in an Agile development environment, collaborating with data scientists, engineers, and business stakeholders.
• Contribute to the growth of our Data Exploitation Practice by implementing cutting-edge data warehousing solutions.

Skills

5+ years data engineering

Python

Scala/Java/C++

Public trust eligibility

Data governance

Education

Bachelor's degree in CS/IS/Engineering or related

Tools

Hadoop

Spark

Kafka

Databricks

PySpark

SparkSQL

Airflow

AWS Redshift

S3

RDS

Glue

Lambda

SQL Server

PostgreSQL

MySQL

Oracle

Job description

Overview

We are seeking a Senior Data Warehouse Engineer to join our team and work closely with clients to develop, optimize, and scale enterprise-grade data platforms, warehouses, and pipelines. We are looking for more than just a “Senior Data Warehouse Engineer,” but a highly skilled data technologist with strong communication and problem-solving abilities who thrives in cloud-based environments.

Responsibilities

• Lead and architect the migration of data environments with a focus on performance, reliability, and scalability.
• Design, implement, and optimize data warehouse solutions, ensuring best practices in data modeling, storage, and retrieval.
• Ability to examine and understand complex data pipelines.
• Assess, document, and analyze data sources, ETL workflows, and business intelligence tools.
• Address technical inquiries related to data warehouse customization, integration, and enterprise architecture.
• Develop and maintain robust data pipelines and ETL processes to support business intelligence and analytics.
• Design and enforce data governance strategies, ensuring high data quality and compliance.
• Work in an Agile development environment, collaborating with data scientists, engineers, and business stakeholders.
• Contribute to the growth of our Data Exploitation Practice by implementing cutting-edge data warehousing solutions.

Qualifications

• Ability to hold a position of public trust with the US government.
• 5-7+ years of experience in data engineering, data warehousing, or data architecture.
• Proficiency in Python or other object-oriented languages such as Scala, Java, or C++.
• Experience designing and implementing data governance strategies.

Preferred:

• Hands-on experience with big data tools such as Hadoop, Spark, and Kafka.
• Expertise in cloud-based data warehouse solutions, preferably AWS (Redshift, S3, RDS, Glue, Lambda).
• Experience with Databricks, PySpark, SparkSQL preferred
• Experience with ETL tools (SSIS or ADF preferred), data pipeline orchestration, and workflow management tools such as Apache Airflow, Luigi, or AWS Step Functions.
• Experience designing data models, schema design, and entity-relationship diagrams.
• Strong knowledge of SQL and database optimization techniques (Preferably SQL Server. Alternatively, PostgreSQL, MySQL, Oracle).
• Bachelor's degree in Computer Science, Information Systems, Engineering, a related technical discipline, or professional experience equivalent.
• Demonstrated ability to lead large-scale data migration efforts.
• Ability to work in a DevSecOps environment, applying CI/CD best practices.