🚨 Urgent Requirement - Spark-based Data Engineer (AWS) - 5-9 years (PySpark, Apache Parquet and Iceberg mandatory) | Remote | FullTime

🚨 Urgent Requirement - Spark-based Data Engineer (AWS) - 5-9 years ( PySpark, Apache Parquet and Iceberg mandatory)

Employment Type: Full time

Experience: 5-9 Years

Work Mode: Remote, India

Job Summary:

5

Key Responsibilities:

• Design, implement, and maintain robust data ingestion pipelines using AWS services (e.g., S3, Glue, EMR) and Spark/PySpark.
• Work extensively with 

  Parquet

   and 

  Apache Iceberg

   to structure, manage, and optimize large datasets for analytical workloads.
• Develop scalable and maintainable ETL workflows to transform raw data into clean datasets optimized for reporting.
• Optimize and schedule Spark jobs for efficient data processing and loading.
• Collaborate with stakeholders and analysts to gather business requirements and translate them into data solutions.
• Prepare datasets for Tableau dashboards, automate Hyper file generation, and manage dashboard refresh pipelines.
• Write high-performance SQL queries and Python scripts for data transformation and validation.
• Ensure data quality, consistency, and lineage across the pipeline.
• Troubleshoot, monitor, and continuously improve data workflows for reliability and performance.
• Document pipelines, schemas, and transformation logic to support transparency and cross-team collaboration.

• 5+ years of hands-on data engineering experience in cloud-native environments (AWS preferred).
• Strong expertise in 

  Apache Spark/PySpark

   for distributed data processing.

• Mandatory experience with Parquet and Apache Iceberg

   for efficient storage and querying of large-scale datasets.
• Proficiency with AWS data tools including S3, Glue, EMR, Redshift, Lambda, and related services.
• Experience with job orchestration tools like Apache Airflow or AWS Step Functions.
• Strong programming skills in 

  Python

   and advanced SQL for data manipulation.
• Solid understanding of data architecture, schema design, and performance tuning.
• Tableau experience including data prep, Hyper file automation, publishing, and refresh management.
• Familiarity with CI/CD pipelines, version control systems (e.g., Git), and Agile development practices.
• Strong problem-solving skills and ability to work collaboratively across technical and business teams

📌 Important Notes

• Candidates with Immediate or 15days Notice Period will be preferred
• Mandatory experience with

  PySpark

  ,

  Parquet

  and

  Apache Iceberg

• PF Account is mandatory for Full Time
• Budget is limited and based on your experience & expertise

📬 Ready to Apply?

Email your resume to career@strive4x.net Use subject line: Spark-based Data Engineer (AWS) -

Include the following in your email:

• Full Name
• Mobile Number
• Current Location
• Total Experience (Years)
• Relevant Experience (Years)
• Current Company
• Current CTC (LPA)
• Expected CTC (LPA)
• Notice Period (Days)
• Do you have a PF account? (Yes/No)
• Are you available to work overlapping IST/US hours?
• Are you fine with Full time?

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