Job Description :

We are looking for an experienced Data Engineer with 5–7 years of experience to design, build, and maintain robust data pipelines and architectures. The ideal candidate will collaborate with data scientists, analysts, and business stakeholders to enable data-driven decision-making and support analytics at scale.


Key Responsibilities

  • Design, develop, and maintain scalable ETL/ELT data pipelines from multiple data sources

  • Build and optimize data warehouses, lakes, and storage solutions (on-premise or cloud)

  • Ensure data quality, integrity, and governance across pipelines and databases

  • Collaborate with data scientists, analysts, and business teams to define data requirements

  • Implement data modeling, schema design, and performance tuning for large datasets

  • Monitor and troubleshoot production data pipelines, ensuring reliability and efficiency

  • Develop and maintain documentation for data architecture, pipelines, and workflows

  • Automate data ingestion, transformation, and reporting processes

  • Stay updated with new data technologies and best practices, recommending improvements

  • Mentor junior data engineers and support team skill development


Required Skills & Qualifications

  • Bachelor’s or Master’s degree in Computer Science, IT, or related field

  • 5–7 years of experience in data engineering, ETL development, or data warehousing

  • Strong SQL skills and experience with relational databases (e.g., PostgreSQL, MySQL, Oracle)

  • Experience with big data technologies: Hadoop, Spark, Kafka, Hive, or similar

  • Proficiency in programming languages like Python, Java, or Scala

  • Experience with cloud platforms: AWS, Azure, or Google Cloud (Redshift, BigQuery, Databricks)

  • Data modeling, schema design, and performance optimization expertise

  • Knowledge of data governance, security, and compliance best practices

  • Excellent problem-solving, analytical, and communication skills



Client : ShrinQ Consulting Group

             

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