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Job Title : Data Engineer

Department : Data Engineering

Location : Chennai

Reports To : Manager Business Intelligence

Position Overview :

Develops effective business intelligence solutions for OEC by designing, developing, and deploying systems to support business intelligence, reporting, data warehousing, and integration with enterprise applications. Implements user access controls and data security measures. Assists in the evaluation of the business to support delivery of effective business intelligence and reporting solutions. Maintains documentation of processes, reports, applications, and procedures.

Key Responsibilities

1. Design and deploy secure, scalable data systems and warehouses using AWS cloud platforms.

2. Create and maintain dashboards, reports, and analytics to support business decisions using Power BI, Amazon QuickSight.

3. Build and optimize ETL / ELT pipelines using services like AWS Glue, Lambda, Step Functions and Event Bridge.

4. Identify opportunities to improve cross-cloud analytics and propose solutions that leverage AWS strengths.

5. Conduct system testing, resolve defects, and ensure smooth integration across cloud environments.

6. Manage data lakes, warehouses, and streaming pipelines using tools such as Redshift, S3, Athena, Kinesis, and EMR.

7. Implement data validation, transformation, and quality assurance across diverse data sources including APIs and databases.

8. Automate infrastructure deployment and management using Terraforms, Infrastructure as Code.

9. Mentor junior engineers, promote best practices, and collaborate within Agile development teams.

Skills & Qualifications

Must-Have :

1. Minimum 5 years of experience in data engineering, including 3+ years working with AWS based solutions.

2. Bachelor’s degree in Computer Science, IT, or a related field from an accredited institution.

3. Strong expertise in Python, SQL, and distributed data processing frameworks like Spark or PySpark.

4. Proven experience developing and testing database components such as stored procedures, triggers, and ETL processes across AWS.

5. Hands-on proficiency with AWS services including S3, Glue, Redshift, and Athena, and orchestration tools like Step Functions or Airflow.

6. Skilled in using BI and analytics tools such as Power BI, Quicksight, SSAS, and Excel.

7. Deep understanding of data modelling, warehousing, data lake architecture, and query languages like DAX / MDX.

8. Familiarity with CI / CD practices for data pipelines, Git-based version control, and Infrastructure as Code tools like Terraform.

Preferred :

• Domain expertise in the company’s industry.
• Certification in AWS.

Perks and Benefits :