AWS Data Architect

3 days ago

Vadodara, Gujarat, India beBeeData Full time ₹ 1,75,00,000 - ₹ 2,25,00,000

Job Title: AWS Data Engineer – Oil

Location: Offshore/REMOTE

Experience: 5+ years

We are seeking an experienced AWS Data Engineer with oil and gas industry expertise to design, build, and optimize scalable data pipelines and cloud solutions.

The ideal candidate will have strong experience in AWS cloud services, data engineering, and knowledge of oil and gas upstream, midstream or downstream processes to support advanced analytics, reporting, and digital transformation initiatives.

Key Responsibilities:


  • Design, develop, and maintain scalable data pipelines and ETL/ELT solutions using AWS cloud services.

  • Ingest, process, and store structured/unstructured data from multiple sources (IoT devices, sensors, ERP systems, drilling logs, production data, etc.).

  • Implement data lake and data warehouse solutions

  • Optimize data pipelines for performance, cost, and scalability.

  • Collaborate with domain experts, data scientists, and business analysts to translate oil and gas business requirements into data solutions.

  • Ensure data governance, data quality, and security compliance.

  • Support real-time data streaming and analytics using AWS services (Kinesis, Kafka, Lambda).

  • Document technical solutions and provide knowledge transfer to the team.

Required Skills and Qualifications:


  • Proficiency in AWS services: S3, Redshift, Glue, Athena, EMR, Lake Formation

  • Lambda, Kinesis, Step Functions, CloudWatch, RDS, DynamoDB (optional)

  • Expertise in ETL/ELT development using PySpark, Python, or SQL.

  • Experience with data modeling, warehousing, and performance tuning.

  • Knowledge of data lake and modern data architecture.

  • Strong SQL skills and ability to work with large datasets.

  • Hands-on with CI/CD and DevOps practices for data solutions.

Benefits:


  • Familiarity with oil and gas industry datasets and use cases (production, drilling, exploration, sensor/IoT data).

  • Understanding of data ingestion patterns.

  • Extensive knowledge of data bricks & Azure Data Factory.

  • SQL Knowledge.

  • Incremental & Append data load.

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