Data Engineer

Ethereum Technologies; Tampa (FL); On-site; USD 91,000 - 124,000; Full time

Job summary

Ethereum Technologies in Tampa, FL is seeking a senior Data Engineer to design, build and optimize data pipelines on Databricks lakehouse. This role requires deep expertise in Spark, Delta Lake, SQL and AWS with a focus on secure, scalable data platforms.

The candidate will model data, support migration from legacy Hadoop ecosystems, implement streaming and batch pipelines (Kafka, Structured Streaming) and manage cost and performance on the Databricks platform.

Qualifications

• 12+ years in data engineering or architecture.
• 5+ years on the Databricks lakehouse platform.
• Strong Spark, Delta Lake and SQL skills; data modeling experience.
• AWS networking, IAM, encryption, multi-account design.
• Migration planning from Hadoop/Hive/warehouse systems.
• Streaming and batch design with Kafka and Structured Streaming.
• Disaster recovery and high-availability design.
• FinOps and Databricks cost modeling with a business case.

Skills

Databricks lakehouse

Spark

Delta Lake

SQL

Data modeling

AWS architecture

Security design

Migration planning

Streaming design

Disaster recovery

Cost modeling

Architecture docs

Tools

Databricks

Kafka

Structured Streaming

IAM

Encryption

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Job Title: Data Engineer
Location: Tampa, FL
Duration: 12 Months + Extension
Bill Rate: $78/hour
Job Type: W-2, 1099, C2C
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EADJob Description :

Must-Have Skills (candidate must meet all)

• Experience:12+ years in data engineering or architecture, with 5+ years on Databricks lakehouse platform.
• Data platform fundamentals:Strong Spark, Delta Lake and SQL, plus data modeling (medallion, dimensional).
• AWS architecture:Networking, IAM, encryption and multi-account design on AWS.
• Secure design:Platform design for PII/NPI, including Unity Catalog access models and lineage.
• Migration:Migration planning from legacy Hadoop/Hive/warehouse systems.
• Streaming and batch design:Ability to choose between batch and streaming (Kafka, Structured Streaming) and design for both.
• Resilience:Disaster recovery and high-availability design.
• Cost modeling:FinOps and Databricks cost and capacity modeling, including a business case.

Communication:Stakeholder management, vendor management and clear architecture documentation

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.