Data Engineering Team Lead

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.