Lead Data Engineer — Real-Time Pipelines & Streaming

Empower; Greenwood Village (CO); Hybrid; USD 125,000 - 182,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Life Insurance

Tuition Reimbursement

401(k) Plan

Paid Time Off

Volunteer Time

Job summary

Empower is seeking a Lead Data Engineer to provide technical leadership in designing scalable data pipelines, real-time ingestion frameworks, and data platforms across enterprise-scale environments.

You will lead complex data initiatives, guide engineers, mentor teams, and collaborate with architects to ensure performance, reliability, and governance, while enabling end-to-end data quality and security.

Qualifications

• Bachelor’s degree in computer science or related field.
• 6–8+ years data engineering on enterprise scale platforms.
• Hands-on with Kafka, Confluent Cloud, AWS Kinesis, or Pulsar.
• Proficient in Python, PySpark, and SQL.

Responsibilities

• Lead design and implementation of data pipelines and real-time streaming solutions.
• Develop and maintain scalable Kafka producers/consumers for sub-second latency.
• Manage CDC using Debezium, AWS DMS, or Qlik Replicate.
• Implement schema evolution and data governance standards.

Skills

Python

PySpark

SQL

Kafka

Confluent Cloud

AWS

Kafka Streams

Spark

ETL/ELT

Data modeling

CI/CD

Docker

Kubernetes

Schema Registry

Mentoring

Agile

Communication

Education

Bachelor’s degree in computer science or related field

Tools

Debezium

Confluent Schema Registry

dbt

Iceberg

Delta Lake

Snowflake

BigQuery

Prometheus

Grafana

Datadog

AWS Kinesis

Apache Pulsar

Job description

Empower is seeking a Lead Data Engineer to provide technical leadership in designing scalable data pipelines, real-time ingestion frameworks, and data platforms across enterprise-scale environments.

You will lead complex data initiatives, guide engineers, mentor teams, and collaborate with architects to ensure performance, reliability, and governance, while enabling end-to-end data quality and security.