zoho_recruit
Senior Fullstack Developer
Agilisium
Tamil Nadu, IND
Full-time
Senior · 4+ years experience
Hybrid
Discovered 3 weeks ago
PythonSQLPySparkDatabricksAWSAirflow
Free
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PythonSQLPySpark
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PythonSQLPySparkDatabricksAWSAirflow
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Introduction to the Role:
Are you passionate about unlocking the power of data to drive innovation and transform business outcomes?
Join our cutting-edge Data Engineering team and be a key player in delivering scalable, secure, and high-performing data solutions across the enterprise.
As a Data Engineer, you will play a central role in designing and developing modern data pipelines and platforms that support data-driven decision-making and AI-powered products.
With a focus on Python, SQL, AWS, PySpark, and Databricks, you'll enable the transformation of raw data into valuable insights by applying engineering best practices in a cloud-first environment.
We are looking for a highly motivated professional who can work across teams to build and manage robust, efficient, and secure data ecosystems that support both analytical and operational workloads.
Accountabilities
- Design, build, and optimize scalable data pipelines using PySpark, Databricks, and SQL on AWS cloud platforms.
- Collaborate with data analysts, data scientists, and business users to understand data requirements and ensure reliable, high-quality data delivery.
- Implement batch and streaming data ingestion frameworks from a variety of sources (structured, semi-structured, and unstructured data).
- Develop reusable, parameterized ETL/ELT components and data ingestion frameworks.
- Perform data transformation, cleansing, validation, and enrichment using Python and PySpark.
- Build and maintain data models, data marts, and logical/physical data structures that support BI, analytics, and AI initiatives.
- Apply best practices in software engineering, version control (Git), code reviews, and agile development processes.
- Ensure data pipelines are well-tested, monitored, and robust with proper logging and alerting mechanisms.
- Optimize performance of distributed data processing workflows and large datasets.
- Leverage AWS services (such as S3, Glue, Lambda, EMR, Redshift, Athena) for data orchestration and lakehouse architecture design.
- Participate in data governance practices and ensure compliance with data privacy, security, and quality standards.
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