Senior Pyspark Data Engineer
3 days ago
About Us
About DATAECONOMY: We are a fast-growing data & analytics company headquartered in Dublin with offices inDublin, OH, Providence, RI, and an advanced technology center in Hyderabad,India. We are clearly differentiated in the data & analytics space via our suite of solutions, accelerators, frameworks, and thought leadership.
Job Description
Job Title:
PySpark Data Engineer
Experience:
8+ Years
Location:
Hyderabad
Employment Type:
Full-Time
Job Summary
We are looking for a skilled and experienced
PySpark Data Engineer
to join our growing data engineering team. The ideal candidate will have 8+ years of experience in designing and implementing data pipelines using
PySpark
,
AWS Glue
, and
Apache Airflow
, with strong proficiency in
SQL
. You will be responsible for building scalable data processing solutions, optimizing data workflows, and collaborating with cross-functional teams to deliver high-quality data assets.
Responsibilities
Key Responsibilities:
- Design, develop, and maintain large-scale ETL pipelines using PySpark and AWS Glue.
- Orchestrate and schedule data workflows using Apache Airflow.
- Optimize data processing jobs for performance and cost-efficiency.
- Work with large datasets from various sources, ensuring data quality and consistency.
- Collaborate with Data Scientists, Analysts, and other Engineers to understand data requirements and deliver solutions.
- Write efficient, reusable, and well-documented code following best practices.
- Monitor data pipeline health and performance; resolve data-related issues proactively.
- Participate in code reviews, architecture discussions, and performance tuning.
Requirements
- 8+ years of experience in data engineering roles.
- Strong expertise in PySpark for distributed data processing.
- Hands-on experience with AWS Glue and other AWS data services (S3, Athena, Lambda, etc.).
- Experience with Apache Airflow for workflow orchestration.
- Strong proficiency in SQL for data extraction, transformation, and analysis.
- Familiarity with data modeling concepts and data lake/data warehouse architectures.
- Experience with version control systems (e.g., Git) and CI/CD processes.
- Ability to write clean, scalable, and production-grade code.
Benefits
Company Standard Benefits.
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