Lead Data Engineer

Empower

4d • $125,400 - $181,875 • Hybrid

About The Position

The Lead Data Engineer will provide technical leadership in the design, development, and optimization of scalable data pipelines, real-time ingestion frameworks, and data platforms. This role will lead complex data initiatives, including event-driven and streaming solutions, while ensuring performance, scalability, reliability, security, data quality, and governance align with enterprise standards. Operating with significant independence, the Lead Data Engineer will guide technical decision-making, mentor engineers, collaborate with architects and stakeholders, and serve as an escalation point for complex data engineering challenges.

Requirements

• Bachelor’s degree in computer science or a related field, or an equivalent combination of training and experience.
• 6-8+ years of data engineering experience with enterprise scale platforms.
• 6-8+ years of hands-on experience with Apache Kafka, Confluent Cloud, AWS Kinesis, or Apache Pulsar.
• Advanced proficiency in Python, PySpark, and SQL.
• Proficiency in Python, Java, Scala, or Go, combined with production experience using Flink, Kafka Streams, or Spark Structured Streaming.
• Strong experience with AWS and modern data platforms.
• Deep expertise with CDC tools such as Debezium and Kafka Connect and log-based replication mechanisms such as Oracle Redo, PostgreSQL WAL, and MySQL binlog.
• Hands-on experience sinking streaming events into modern lakehouse formats such as Apache Iceberg and Delta Lake and cloud warehouses such as Snowflake or BigQuery.
• Solid foundation in Docker, Kubernetes, Terraform, and CI/CD automation for event-driven microservices.
• Experience implementing data contracts and schema management using tools such as Schema Registry to support end-to-end data quality, schema evolution, and interface reliability.
• Deep understanding of data modeling, ETL/ELT processes, and data warehousing.
• Experience leading technical initiatives and mentoring engineers.
• Strong problem-solving and communication skills.
• Experience working in Agile environments.

Nice To Haves

• Experience integrating AI agents to self-heal pipeline failures, dynamically resolve schema drift, and extract structured data from unstructured event streams.
• Experience designing resilient fallback strategies, including automated dead-letter reprocessing, circuit breakers, and deterministic idempotency keys.
• Experience championing domain-driven event design, including Event Sourcing and CQRS, and defining enterprise-wide event contracts and governance.
• Experience establishing and formalizing data contracts between producers and consumers and leading adoption of schema registry practices for lifecycle versioning and backward and forward compatibility.

Responsibilities

• Lead the design and implementation of advanced data pipelines, ingestion frameworks, and real-time streaming solutions.
• Build, tune, and maintain scalable Kafka producers and consumers using Python, Java, Go, or Scala to support sub-second latency and high availability across distributed services.
• Configure and manage enterprise change data capture (CDC) solutions, including Debezium, AWS DMS, or Qlik Replicate, across relational and NoSQL source systems such as PostgreSQL, MySQL, MongoDB, and Oracle into Kafka topics.
• Develop stream-processing logic using Apache Flink, Spark Streaming, Kafka Streams, or dbt-mesh architectures to enrich, filter, and aggregate event payloads in flight.
• Implement and enforce schema evolution policies using Confluent Schema Registry with Avro, Protobuf, or JSON Schema, and support appropriate delivery guarantees and idempotency across consumers.
• Integrate automated code generation, validation agents, and LLM-driven orchestration using technologies such as LangGraph, AutoGen, or CrewAI to support schema drift, unstructured event parsing, and dynamic routing within event streams.
• Instrument pipelines with end-to-end monitoring and alerting using tools such as Prometheus, Grafana, or Datadog, and manage consumer group offsets, partition rebalancing, and dead-letter queues.
• Guide the technical execution of complex data initiatives across teams and translate highly complex business requirements into scalable data solutions.
• Ensure data platforms are optimized for performance, scalability, reliability, and high availability.
• Enforce data governance, security, quality, data contract, and schema management standards.
• Mentor engineers, provide technical leadership on projects, and lead code reviews to ensure adherence to engineering standards.
• Collaborate with architects and stakeholders to align solutions with enterprise direction and contribute to architectural and design decisions.
• Drive improvements in automation, efficiency, and platform capabilities.
• Complete other duties as assigned.

Benefits

• Medical, dental, vision and life insurance
• Retirement savings – 401(k) plan with generous company matching contributions (up to 6%), financial advisory services, potential company discretionary contribution, and a broad investment lineup
• Tuition reimbursement up to $5,250/year
• Business-casual environment that includes the option to wear jeans
• Generous paid time off upon hire – including a paid time off program plus ten paid company holidays and three floating holidays each calendar year
• Paid volunteer time — 16 hours per calendar year
• Leave of absence programs – including paid parental leave, paid short- and long-term disability, and Family and Medical Leave (FMLA)
• Business Resource Groups (BRGs) – BRGs facilitate inclusion and collaboration across our business internally and throughout the communities where we live, work and play. BRGs are open to all.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior