Note: The job is a remote job and is open to candidates in USA. Dice is investing in the next evolution of their data, analytics, and artificial intelligence ecosystem. They are seeking a Lead Data Engineer to shape enterprise analytics strategy, influence architecture, and partner with the business to drive smarter decisions.
Responsibilities
- Design and lead enterprise-grade pipelines, supporting both batch and streaming data processing
- Own the full ETL/ELT lifecycle, from design through production support
- Drive data engineering standards, best practices, and architecture across the data ecosystem
- Translate business requirements into scalable, high-performance data solutions
- Mentor a small team while remaining hands-on; and
- Ensure data reliability, performance, governance, and cost optimization
Skills
- 10+ years of IT experience, including deep expertise in data engineering & ETL
- 4-6+ years of recent hands-on experience in designing, building, and scaling data pipelines
- Strong hands-on experience with Databricks (Spark, Delta Lake, Unity Catalog) and AWS (S3, IAM, networking)
- A passion for continued learning and an interest in staying current with the rapidly evolving data and analytics space
- Experience working in an Agile analytics environment where close collaboration with key stakeholders to address evolving requirements is the norm
- Expertise in SQL, Python, data modeling, and distributed processing
- Experience with CI/CD, DevOps, and modern data architecture (lakehouse, medallion, etc.)
- Strong communication skills and the ability to translate complex technical concepts into solutions that deliver business outcomes
- You're analytical, curious, and solutions-oriented
- You thrive in environments where you balance priorities and drive outcomes
- You're comfortable with ambiguity and can quickly learn the business
- You build strong partnerships and bring a “get things done” mindset
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