DATAECONOMY

AWS Data Engineer

DATAECONOMY Hyderabad, Telangana, India

Information Technology & Services · 201-500 employees

Oct 14
data-engineer Senior (5-10 yrs) Full-time India
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About the role

Develop, maintain, and optimize scalable ETL/ELT data processing pipelines using Python and PySpark. Collaborate with cross-functional teams to integrate data from multiple sources while ensuring data quality and performance optimization.

What they look for

Python PySpark AWS SQL ETL ELT Apache Spark Data warehousing Data pipelines Git Agile Performance tuning Data modeling Cloud computing Distributed computing

Requirements

Requires a degree in BTech, MTech, or MCA with 4-6 years of experience in data engineering. Candidates must possess strong programming skills in Python and PySpark, along with expertise in SQL and distributed computing architectures.

Benefits

Comprehensive medical coverage Group personal accident insurance Group term life insurance Provident fund Gratuity Flexible work options Annual leave Company-declared holidays Refreshments

Full description

Job Title: Data Engineer Experience Level: 4 - 6 years Location: Hyderabad / Pune

Qualification: BTech/MTech/MCA Mode of Work: Hybrid

We are seeking an experienced AWS Data Engineer with deep expertise in Banking, Financial Services, and Insurance systems. The candidate must be familiar at least in one Data ware housing concepts such as ODS/Marts and must have done at least one end-to-end data processing pipeline designing. He/she should be capable of handling the ETL design and implementation solely and would work towards creating a positive and innovation friendly environment. The incumbent would be responsible for creating new capabilities.

Responsibilities

  • Develop, maintain, and optimize data processing applications using Python and PySpark.
  • Build scalable ETL/ELT pipelines to process large volumes of structured and unstructured data.
  • Perform data extraction, cleansing, transformation, aggregation, and validation.
  • Work with Apache Spark for distributed data processing and large-scale data transformations.
  • Write complex SQL queries and optimize database operations.
  • Develop reusable Python modules, functions, and libraries.
  • Optimize Spark jobs by analyzing execution plans, partitioning, caching, and performance bottlenecks.
  • Work with file formats such as CSV, JSON, Parquet.
  • Integrate data from multiple sources, including databases, APIs, and cloud storage.
  • Implement error handling, logging, monitoring, and data quality checks.
  • Collaborate with data engineers, data architects, analysts, and business stakeholders.
  • Follow coding standards, version control practices, and Agile development methodologies.

Requirements

Requirements

  • Strong programming knowledge in Python, including functions, OOP, exception handling, and data structures.
  • Hands-on experience with PySpark DataFrames, Spark SQL, transformations, and actions.
  • Good understanding of Apache Spark architecture and distributed computing.
  • Strong SQL skills, including joins, sub queries, CTEs, and window functions.
  • Experience developing ETL/ELT pipelines and handling large datasets.
  • Knowledge of data processing formats such as Parquet, JSON, and CSV.
  • Experience with Git and software development best practices.
  • Understanding of debugging, performance tuning, and troubleshooting.

Preferred Skills

  • Experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Familiarity with Databricks, Azure Data Factory, AWS Glue, or similar data engineering tools.
  • Knowledge of data warehouses and lake house architectures.
  • Experience with Airflow or other workflow orchestration tools.
  • Familiarity with CI/CD pipelines, Docker, and automated testing.
  • Knowledge of Delta Lake, Kafka, or streaming data processing.

Benefits

  • ​Comprehensive Medical Coverage:

Health insurance of INR 5.0 Lakhs for you and your family (up to 6 members), ensuring complete peace of mind.

  • Robust

Protection Plans:

Group Personal Accident Insurance and Group Term Life Insurance to safeguard you and your loved ones.

  • Retirement Benefits:

PF and Gratuity provided as per standard government regulations.

  • Flexible

Work Options:

Enjoy hybrid work arrangements & flexible working hours

  • Generous

Leave Policy:

21 days of annual leave, in addition to 10 company-declared holidays.

  • Employee

Well-being Spaces:

Access to a dedicated break-out area with round-the-clock refreshments for relaxation and rejuvenation.

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