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Senior Data Engineer (AWS)

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Onsite

Senior Data Engineer (AWS)

INTELSOL

Senior Data Engineer (AWS)

Skills

SQL QueriesBig DataData EngineeringPythonAWS LambdaKafkaSnowflakeAmazon RedshiftData AnalysisAWSPySparkAWS KinesisApache AirflowTerraform

8 months ago

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Important information


Location:

Bucharest, Romania

Work mode:

Onsite

Published on:

13 September 2026

What they need


Client: IT Services Center

Office Location: Bucharest

Contract Duration: At least 12 months

Project No.: 001120925

General

We are looking for Senior Data Engineers to join our client’s Data Team, contributing to the design, development, and optimization of scalable data pipelines. The ideal candidate will have expertise in big data technologies, AWS cloud services, and data engineering best practices enabling efficient data transformation, warehousing, and analytics.

Responsibilities/Activities

  • Design, develop, and maintain scalable, high-performance data pipelines using Python, PySpark
  • Design, build, and optimize ETL/ELT pipelines and data transformation processes using SQL and ETL frameworks to ensure performance, scalability, and cost-efficiency, while supporting data warehousing solutions
  • Work with big data processing technologies such as Apache Spark on AWS Glue and EMR
  • Utilize Amazon S3, AWS Glue, and AWS Lake Formation for scalable data storage and analytics
  • Design and implement data models to support Data Warehousing (Redshift) and Business Intelligence (BI) needs
  • Ensure data quality, validation, and optimization to maintain reliability and consistency
  • Leverage AWS cloud-native services (Lambda, Step Functions, Kinesis) to build scalable data solutions
  • Collaborate with BI and analytics teams to ensure seamless data accessibility and insights delivery
  • Implement CI/CD pipelines for automated deployment, monitoring, and management of data solutions

Requirements

Technical

  • At least 5 years of experience in Data Engineering
  • Strong proficiency in Python and PySpark
  • Experience with workflow orchestration (Apache Airflow, AWS Step Functions)
  • Expertise in AWS Data Lake & Warehouse stack (S3, Glue, Redshift, EMR, Athena)
  • Experience with BI tools (QuickSight preferred)
  • Advanced SQL skills for data manipulation, validation, and optimization
  • Strong knowledge of ETL best practices, Data Modeling, and Data Warehousing
  • Proven ability to scale ETL pipelines
  • Solid understanding of CI/CD pipelines and DevOps principles

Education

  • University degree in Computer Science, Mathematics or another related field

Others

  • Good level of English (oral and written)
  • Strong analytical and problem-solving skills
  • Ability to quickly learn and adapt to new technologies
  • Ability to work in a fast-paced, agile environment

Nice to have requirements

  • Experience with streaming data solutions (Kafka, Pub/Sub)
  • Experience with Snowflake
  • Knowledge of Terraform and/or CloudFormation
  • Experience in the financial-banking industry

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