Data Engineer

Ejamerica; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Ejamerica is seeking an experienced Data Engineer to advance our enterprise data platform on the Databricks Lakehouse Platform. You will design, build, and optimize scalable data pipelines, implement Delta Lake data models, and enable advanced analytics, AI/ML initiatives, and enterprise-wide data products.

This role collaborates with Data Architects, Scientists, BI teams, and business stakeholders to deliver governed, reusable data assets across Operations, Finance, Asset Management, Safety,

Qualifications

• 7+ years of data engineering experience.
• Experience with Databricks Lakehouse Platform.
• Strong knowledge of ETL/ELT development.
• Experience with data governance and security.

Responsibilities

• Design, build, and maintain scalable data pipelines using Databricks, PySpark, and Spark SQL.
• Develop ETL/ELT processes that ingest, transform, and curate large-scale data.
• Implement and support Medallion Architecture (Bronze, Silver, Gold).
• Develop Delta Lake-based solutions with data quality controls.
• Build batch and near real-time data processing using Spark Streaming and Kafka.
• Create reusable frameworks for data ingestion, monitoring, and orchestration.

Skills

Analytical thinking

Problem-solving

Communication with stakeholders

Collaboration

Self-motivated

Continuous learning

Tools

Databricks

PySpark

Spark SQL

Python

SQL

Delta Lake

Unity Catalog

Delta Live Tables

Job description

NS Job Title: Data Engineer

Experience: 7+ years

Position Summary

Seeking an experienced Databricks Engineer to support the modernization of our enterprise data platform as part of our cloud transformation journey. The ideal candidate will design, develop, and optimize scalable data solutions on the Databricks Lakehouse Platform while enabling advanced analytics, AI/ML initiatives, and enterprise-wide data products.

This role will work closely with Data Architects, Data Scientists, Business Intelligence teams, and business stakeholders to deliver high-quality, governed, and reusable data assets supporting Operations, Transportation, Finance, Asset Management, Safety, and Corporate Services.

Key Responsibilities

• Design, build, and maintain scalable data pipelines using Databricks, PySpark, and Spark SQL.
• Develop ETL/ELT processes that ingest, transform, and curate large-scale structured and unstructured datasets.
• Implement and support Medallion Architecture (Bronze, Silver, Gold layers).
• Develop Delta Lake-based solutions with optimized performance and data quality controls.
• Build batch and near real-time data processing solutions leveraging Spark Streaming and Kafka.
• Create reusable frameworks and automation for data ingestion, monitoring, and orchestration.

Databricks Platform Management

• Develop and maintain Databricks notebooks, workflows, jobs, and clusters.
• Implement and manage Unity Catalog, access controls, and data governance standards.
• Configure Delta Live Tables (DLT) and streaming pipelines.
• Support environment promotion across Dev, QA, UAT, and Production.
• Collaborate with platform teams on performance tuning and cost optimization initiatives.
• Integrate data from multiple enterprise sources including:
• SAP
• Mainframe
• DB2
• SQL Server
• Oracle
• Tibco
• Kafka
• REST APIs
• Design and implement cloud-native integrations supporting client data modernization strategy.
• Work with Azure and AWS cloud services supporting Databricks workloads.

Data Quality & Governance

• Implement data validation, reconciliation, and monitoring controls.
• Develop automated data quality frameworks and exception handling.
• Support data lineage, metadata management, and governance initiatives.
• Ensure compliance with enterprise security and regulatory requirements.
• Engage with business teams to understand analytics requirements and translate them into scalable technical solutions.
• Work closely with Data Scientists and BI developers to enable advanced analytics and reporting.
• Mentor junior data engineers and establish engineering best practices.
• Participate in Agile ceremonies and contribute to solution design discussions.

Required Qualifications{

Experience: 7+ years.

Technical Skills

• Databricks Workspaces
• Databricks Notebooks
• Databricks Jobs & Workflows
• Unity Catalog
• Databricks SQL
• PySpark
• Spark SQL
• Python
• SQL
• ETL/ELT Development
• Data Modeling
• Data Warehousing Concepts

Streaming & Messaging

• Spark Streaming
• ADLS Gen2
• AWS S3
• IAM

Databases

• SQL Server
• Oracle
• DB2
• BigQuery (preferred)
• Snowflake (preferred)

DevOps

• Git
• GitHub Actions
• Infrastructure as Code (preferred)

Preferred Qualifications

• Databricks Certified Data Engineer Associate or Professional.
• Experience supporting Large Enterprise Data Modernization programs.
• Experience migrating workloads from Teradata or legacy platforms to Databricks.
• Familiarity with SAP Datasphere, SAP BW, or SAP BDC integrations.
• Exposure to AI/ML workloads and feature engineering on Databricks.

Soft Skills

• Strong analytical and problem-solving skills.
• Ability to communicate technical concepts to business stakeholders.
• Strong collaboration and teamwork skills.
• Self-motivated with the ability to work independently.
• Continuous learning mindset and passion for modern data technologies