Urgent Requirement

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:
We are looking for a seasoned Data Engineer with a minimum of 5 years of experience to build, manage, and optimize scalable data pipelines on AWS using Apache Spark/PySpark. The ideal candidate must have hands-on expertise in working with  Parquet  and  Apache Iceberg  file formats/tables, and should be capable of delivering end-to-end data solutions that support analytics and reporting through Tableau dashboards.
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.
Required Skills and Experience:
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 Use subject line: Spark-based Data Engineer (AWS) -
Include the following in your email:
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Total Experience (Years)
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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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