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TalentBox Labs
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Data Engineer - ETL/SQL/Python (2-7 yrs)
TalentBox Labs
posted 14hr ago
Key skills for the job
Job Description : Data Engineer
Role Overview :
We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. This role involves working with modern cloud technologies, ETL/ELT processes, and big data frameworks to ensure efficient data integration and transformation. The ideal candidate should have strong expertise in SQL, Python, Spark, and cloud-based data platforms.
Key Responsibilities :
- Data Pipeline Development : Design, develop, and maintain scalable ETL/ELT data pipelines for ingesting, processing, and storing large datasets.
- Cloud Data Engineering : Work with cloud platforms (AWS, Azure, GCP) to build and optimize data storage solutions such as data lakes and warehouses.
- Database Management : Develop and optimize SQL queries, stored procedures, and data transformations across relational (MySQL, PostgreSQL, SQL Server) and NoSQL databases.
- Big Data Processing : Utilize tools like Apache Spark, Databricks, Hadoop, and Kafka to process and analyze large volumes of structured and unstructured data.
- Automation & Performance Tuning : Automate data workflows, optimize ETL processes, and improve performance for data ingestion and transformations.
- Data Quality & Governance : Implement data validation, monitoring, and governance best practices to ensure accuracy, security, and compliance.
- Collaboration & Support : Work with data scientists, analysts, and software engineers to enable data-driven decision-making across teams.
Required Skills & Qualifications :
- Strong expertise in SQL, Python, and Spark for data processing and analytics.
- Experience with cloud-based data services (AWS Redshift, Azure Synapse, Google BigQuery, etc.).
- Hands-on experience with ETL tools like Apache Airflow, Informatica, Talend, or FiveTran.
- Knowledge of data modeling, warehousing concepts, and distributed computing.
- Familiarity with DevOps, CI/CD pipelines, and containerization (Docker, Kubernetes) is a plus
Functional Areas: Software/Testing/Networking
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