Posted:1 month ago|
Platform:
Work from Office
Full Time
• Strong hands-on experience in Python programming and PySpark • Experience using AWS services (RedShift, Glue, EMR, S3 & Lambda) • Experience working with Apache Spark and Hadoop ecosystem. • Experience in writing and optimizing SQL for data manipulations • Good Exposure to scheduling tools. Airflow is preferable. • Must Have Data Warehouse Experience with AWS Redshift or Hive • Experience in implementing security measures for data protection. • Expertise to build/test complex data pipelines for ETL processes (batch and near real time) • Readable documentation of all the components being developed. • Knowledge of Database technologies for OLTP and OLAP workloads
Good understanding of Data warehouse and Data Lakes • Familiarize ETL tools like Netezza or Informatica. • Experience working with NoSQL databases like DynamoDB or MongoDB. • Good to have exposure to AWS services (Step Functions, Athena) • Data Modelling exposure • Familiarity with Investment Banking domain
1Create and maintain optimal data pipeline architecture for efficient and reliable data processing.
2 Assemble large, complex data sets that meet functional / non-functional business requirements.
3 Database management, ETL process, Data modelling, ensuring data quality and integrity.
4 Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
5 Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Tata Consultancy Services
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