Data Engineering Team Lead

UNAVAILABLE; McLean (VA); On-site; USD 150,000 - 190,000; Full time

Job summary

UNKNOWN company is seeking a seasoned Data Engineering Team Lead to drive enterprise-grade data platforms and pipelines. You will mentor a team, define best practices, and act as the technical liaison for data product customization and integration strategies.

You will lead design, development, and optimization of scalable data solutions using Databricks and cloud services, while leveraging Purview for data cataloging and governance.

Qualifications

• Must have seasoned data engineering background with leadership experience.
• Strong communication and customer service mindset for stakeholder interactions.
• Bachelor's degree and 10+ years of total experience.

Responsibilities

• Lead and mentor a team of data engineers to deliver complex migrations.
• Oversee ETL processes, data warehousing, and BI tooling design.
• Define standards for cloud-based data platforms (AWS/Azure/GCP).
• Guide Databricks-based data solution development and optimization.
• Coach team members and drive Agile practices across sprints.

Skills

Data engineering leadership

Mentorship

ETL design

Python

Spark

SQL

Java

Scala

Cloud platforms

Leadership and communication

Education

Bachelor's degree

Tools

Databricks

Purview

Airflow

Azkaban

Postgres

Cassandra

Kafka

Job description

Overview

We are looking for a seasoned Data Engineering Team Lead to work with our team and our clients to develop enterprise grade data platforms, services, and pipelines. We are looking for more than just a "Data Engineering Team Lead", we need a technologist with excellent communication and customer service skills and a passion for data, problem solving, and mentorship.

Responsibilities

• Lead, mentor, and provide technical oversight for a team of data engineers, ensuring successful delivery of complex data environment migrations with optimal performance and reliability.
• Oversee and guide the assessment, design, and optimization of ETL processes, workflows, business intelligence tools, and reporting solutions.
• Act as the primary technical liaison for addressing strategic inquiries related to data product customization, integration strategies, enterprise architecture alignment, and overall functionality.
• Define best practices and technical standards for cloud-based database and data warehousing solutions leveraging platforms such as AWS, Azure, or GCP.
• Lead the design, development, and optimization of scalable data solutions using Databricks.
• Leverage Microsoft Purview to support data cataloging, lineage, metadata management, and integration across the data environment.
• Set technical direction, conduct code reviews, and coach team members.
• Facilitate Agile methodologies and development practices across the data engineering team, coordinating sprints, backlog grooming, and iterative delivery cycles.
• You will contribute to the growth of our AI & Data Exploitation Practice!

Qualifications

• Ability to obtain and maintain a U.S. government security clearance.

• Bachelor's degree and 10+ years of total experience.

• 8+ years of direct experience in Data Engineering, including experience with tools such as:

  • Big data tools: Hadoop, Spark, Kafka, etc.

  • Relational SQL and NoSQL databases, including Postgres and Cassandra.

  • Data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.

  • Cloud services across AWS, Azure, or GCP.

  • Data streaming systems: Storm, Spark-Streaming, etc.

  • Search tools: Solr, Lucene, Elasticsearch.

  • Programming and scripting languages: Python, Java, C++, Scala, etc.

• Experience with Microsoft Purview.

• Experience with Databricks.

• Experience with Wiz or similar cloud security platforms, such as Palo Alto Cortex, preferred.

• Advanced working SQL knowledge and experience working with relational databases, query authoring and optimization (SQL), as well as working familiarity with a variety of databases.

• Experience with message queuing, stream processing, and highly scalable ‘big data’ data stores.

• Experience manipulating and processing large, disconnected structured and unstructured datasets to support analysis and extract value.

• Experience constructing complex queries to analyze results using databases or in a data processing development environment.

• Experience with data modeling tools and processes.

• Experience architecting transactional data systems and data warehouses.

• Experience aggregating results and/or compiling information for reporting from multiple datasets.

• Experience working in an Agile environment.

• Experience mentoring and coaching Data Engineers.

• Experience supporting project teams of developers and data scientists building web-based interfaces, dashboards, reports, and analytics/machine learning models.