Job Description

We are looking for a skilled Data Engineer with 6+ years of experience in big data technologies, particularly Python, PYSpark, SQL, and data lakehouse architectures. The ideal candidate will have a strong background in building scalable data pipelines and experience with modern data storage formats, including Apache Iceberg. You will work closely with cross-functional teams to design and implement efficient data solutions in a cloud-based environment.

Data Pipeline Development

The core responsibilities for the job include the following:

  • Design, build, and optimize scalable data pipelines using Apache Spark.
  • Implement and manage large-scale data processing solutions across data lakehouses.

Data Lakehouse Management

  • Work with modern data lakehouse platforms (e. g. Apache Iceberg) to handle large datasets.
  • Optimize data storage, partitioning, and versioning to ensure efficient access and querying.

SQL And Data Management

  • Write complex SQL queries to extract, manipulate, and transform data.
  • Develop performance-optimized queries for analytical and reporting purposes.

Data Integration

  • Integrate various structured and unstructured data sources into the lakehouse environment.
  • Work with stakeholders to define data needs and ensure data is available for downstream consumption.

Data Governance And Quality

  • Implement data quality checks and ensure the reliability and accuracy of data.
  • Contribute to metadata management and data cataloging efforts.

Performance Tuning

  • Monitor and optimize the performance of Spark jobs, SQL queries, and overall data infrastructure.
  • Work with cloud infrastructure teams to optimize costs and scale as needed.

Requirements

  • Bachelors or Masters degree in Computer Science, Information Technology, or a related field.
  • 8+ years of experience in data engineering, with a focus on Java/Python, Spark, and SQL Programming languages.
  • Hands-on experience with Apache Iceberg, Snowflake, or similar technologies.
  • Strong understanding of data lakehouse architectures and data warehousing principles.
  • Proficiency in AWS data services.
  • Experience with version control systems like Git and CI/CD pipelines.
  • Excellent problem-solving and analytical skills.
  • Strong communication and collaboration skills.

Nice To Have

  • Experience with containerization (Docker, Kubernetes) and orchestration tools like Airflow.
  • Certifications in AWS cloud technologies.

This job was posted by Ankita Swain from Sigmoid.


Job Details

Role Level: Mid-Level Work Type: Full-Time
Country: India City: Bengaluru ,Karnataka
Company Website: https://www.sigmoid.com/ Job Function: Engineering
Company Industry/
Sector:
Hotels And Motels And Business Consulting And Services

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