Lead Consultant Data Engineer (DHS)

Overview

Lead Data Engineers at Excella play a key role in designing and building modern data solutions, including data lakes and cleansed data repositories. They develop robust, scalable, and sustainable data pipelines using batch and streaming technologies. Senior Data Engineers collaborate with cross-functional teams, including Architects, Data Scientists, and DevOps, to ensure data availability, quality, and integration.

Responsibilities

• Develop and manage data processes to ensure availability and usability.
• Create and automate data pipelines and platforms.
• Write clean, efficient, and well-documented code to support data engineering solutions.
• Monitor and ensure data quality through automated testing frameworks.
• Collaborate with Architects, Product Owners, Data Scientists, and DevOps to design, build, and maintain scalable data solutions.
• Research data acquisition sources and evaluate suitability.
• Integrate data management solutions into client environments.
• Identify and mitigate risks to data while ensuring data recovery plans.
• Build and maintain data repositories, including data warehouses, data lakes, and operational data stores.

Qualifications

• 8+ years of professional experience in data engineering or related fields.
• Proven ability to build robust, scalable data pipelines and production-grade ETL/ELT systems.
• Strong proficiency in SQL, Python, and orchestration tools like Airflow and dbt.
• 2+ years of hands-on experience with Databricks, including development, data processing, and pipeline optimization in a cloud-based environment.
• Hands-on experience with big data technologies such as Spark, Kafka, and file formats like Parquet, Delta Lake, and Iceberg.
• Deep experience with AWS cloud data platforms (e.g., AWS Glue, S3, Redshift, EMR, BigQuery, or Azure equivalents).
• Solid understanding of data modeling, performance optimization, and designing secure, well-structured data stores.
• Familiarity with data lake and analytical architecture patterns, including Star Schema, schema-on-read, and data quality frameworks.
• Experience with CI/CD, Git, infrastructure-as-code (e.g., Terraform), and NoSQL databases.
• Effective communicator with experience working in Agile environments (Scrum/Kanban) and collaborating across technical and non-technical teams.
• Strong problem-solving skills, a growth mindset, and a passion for learning new technologies.
• One or more of the following certifications:
• AWS Certified Machine Learning - Specialty
• Data Science Council of America (DASCA) Certifcations
• Databricks Certified Machine Learning Associate
• Databricks Certified Developer for Apache Spark
• Databricks Certified Data Engineer Associate
• Databricks Certified Data Engineer Professional
• AWS Certified Data Analytics - Specialty
• Python or Scala Programming Certification
• Ability to hold and maintain a DHS Public Trust (requires US Citizenship)

Pay Range

$138,000 - $185,000 USD