Aptino
Aptino

Lead Data Engineer

Cincinnati, OH, US • Posted 5 hours ago • Updated 5 hours ago
Contract Corp To Corp
Contract Independent
Contract W2
12 Months
No Travel Required
On-site
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Extract, Transform, Load
  • Data Processing
  • Data Quality
  • Data Validation
  • Data Engineering
  • Data Integration
  • Data Modeling
  • Cloud Computing
  • Performance Tuning
  • Problem Solving
  • Migration
  • Netezza
  • Offshoring
  • Optimization
  • Legacy Systems
  • Management
  • Mentorship
  • Microsoft Azure
  • Google Cloud
  • Google Cloud Platform
  • IBM
  • IT Management
  • Databricks
  • Design Patterns
  • Good Clinical Practice
  • Communication
  • Conflict Resolution
  • Data Warehouse
  • Analytics
  • PySpark
  • Python
  • Scripting
  • Apache Spark
  • Automated Testing
  • Caching
  • ELT
  • SQL
  • Specification Gathering
  • Storage
  • Stored Procedures
  • Testing
  • Workflow
  • IBM Netezza
  • Netezza to Databricks Migration
  • Data Warehousing
  • ETL/ELT
  • Data Platform Modernization
  • Data Warehouse Migration
  • Databricks Workflows
  • Delta Lake
  • Lakehouse Architecture
  • Data Pipeline Development
  • Data Transformation
  • Legacy SQL Conversion
  • Spark Optimization
  • Source-to-Target Reconciliation
  • Migration Testing
  • Cutover Planning
  • Production Support
  • Azure
  • Google Cloud Platform (GCP)
  • Cloud Data Engineering
  • Distributed Data Processing
  • Onshore/Offshore Team Leadership
  • Technical Leadership
  • Vendor Management
  • Team Mentoring
  • Code Reviews
  • Deployment Management
  • Troubleshooting
  • Stakeholder Management
  • Technical Documentation
  • ETL/ELT Development
  • Data Platform Migration
  • Data Modernization
  • Data Pipeline Optimization
  • GCP
  • Data Reconciliation
  • Migration Cutover
  • Vendor Coordination
  • Deployment
  • Stakeholder Communication

Summary

Role: Lead Data Engineer

Location: Cincinnati, OH (Onsite)
Duration: 12 Months

Role Overview:

We are seeking an experienced Lead Data Engineer with strong hands-on expertise in Databricks, Apache Spark, SQL, and Python/PySpark to lead enterprise data modernization initiatives, particularly migrating legacy data warehouse platforms such as IBM Netezza to Databricks. The ideal candidate will combine technical leadership, large-scale data engineering expertise, and experience managing distributed onshore and offshore teams.

Key Responsibilities:

  • Lead onshore and offshore data engineering teams across client organizations, implementation partners, and multiple vendors.

  • Drive end-to-end migration of legacy data warehouse workloads from IBM Netezza to Databricks.

  • Convert business requirements and architecture designs into technical specifications, development plans, and engineering deliverables.

  • Design, develop, and optimize scalable ETL/ELT pipelines, data transformations, and workflows using Databricks, Spark, SQL, and Python/PySpark.

  • Modernize legacy SQL queries, stored procedures, scripts, and data processing logic for execution on Databricks.

  • Implement data quality checks, automated testing, performance tuning, and coding standards to ensure reliable and efficient data pipelines.

  • Coordinate with architects, project managers, business stakeholders, and vendor teams to manage technical dependencies and delivery milestones.

  • Mentor junior and mid-level engineers, conduct code reviews, and provide technical guidance.

  • Support deployment activities, production troubleshooting, incident resolution, and ongoing pipeline maintenance.

  • Lead data validation, source-to-target reconciliation, migration cutover, and post-deployment stabilization.

  • Leverage Azure and Google Cloud Platform cloud services to support data integration, storage, and modernization initiatives.

Required Qualifications:

  • 8+ years of experience in data engineering, data warehousing, ETL/ELT development, or analytics engineering.

  • 2+ years of experience leading onshore/offshore teams and coordinating distributed engineering groups.

  • Strong hands-on expertise in Databricks (mandatory), Apache Spark, SQL, Python, and PySpark.

  • Experience with IBM Netezza or comparable enterprise data warehouse platforms.

  • Proven experience in data warehouse migration, cloud data platform modernization, or legacy system transformation.

  • Strong understanding of data pipelines, Lakehouse architecture, distributed processing, and data modeling.

  • Familiarity with Azure and Google Cloud Platform (Google Cloud Platform).

  • Excellent communication, technical leadership, problem-solving, and troubleshooting skills.

Preferred Skills:

  • Experience migrating Netezza SQL workloads and legacy ETL processes to Databricks.

  • Knowledge of Spark optimization, partitioning, caching, job performance tuning, and scalable data processing.

  • Familiarity with Databricks workflows, Delta Lake, and modern Lakehouse design patterns.

  • Experience with migration testing, data reconciliation, production deployment, and cutover planning.

  • Ability to manage multiple vendors, mentor engineers, and deliver projects in a collaborative, onsite environment.

Important: Hands-on Databricks expertise is a mandatory requirement for this role.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90999382
  • Position Id: 9114543
  • Posted 5 hours ago
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AK

Anchal Khapekar

Recruiter @ Aptino

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