Manager

Lead data engineering strategy across multiple projects and teams. Drive innovation in data engineering practices and model optimization. Represent the data engineering team in executive meetings. Develop long-term plans for data engineering and data infrastructure. Key Responsibilities • Ability to design, build and unit test applications on Spark framework on Python. • Build Python and PySpark based applications based on data in both Relational (Oracle, SQL Server) and NoSQL database e.g. Redis, Valkey • Build ingestion pipelines to load data into in-memory caching database. • Build data pipelines to load and export data to/from the Master Data Management or Reference Data Management Platform using PySpark • Hands on experience doing at least one MDM implementation using TIBCO, Informatica, GoldenSource or custom-built MDM/RDM platforms • Experience with designing/building Data APIs and its interaction with data consumers • Optimize performance of the built Spark applications using configurations around Spark Context, Spark-SQL and Data Frame. • Build Python programs using module libs e.g. pandas, requests, json, flask, pickle • Experience in processing large amounts of structured data, including integrating data from multiple sources. • Ability to design & build real-time applications using REST API, JSON, XML • Ability to build solutions on AWS services using Glue ETL, Lambda functions on Python • Create and maintain integration and regression testing framework on Jenkins integrated with BitBucket and/or GIT repositories • Participate in the agile development process, and document and communicate issues and bugs relative to data standards in scrum meetings • Work collaboratively with onsite and offshore team. • Develop & review technical documentation for artifacts delivered. • Ability to solve complex data-driven scenarios and triage towards defects and production issues • Participate in code release and production deployment. • Challenge and inspire team members to achieve business results in a fast paced and quickly changing environment Requirements • BE/B.Tech/ B.Sc. in Computer Science/ Statistics, Econometrics from an accredited college or university. • Minimum 4 years of extensive experience in design, build and deployment of PySpark-based applications. • Hands-on experience in Redis, Valkey, OpenSearch database • In-depth knowledge of Python core programming language – lists, dictionaries, tuples • Expertise on Python libraries e.g. pandas, requests, json, flask, pickle • Good understanding on Informatica PowerCenter for building data pipelines • Understanding of Master Data Management processes & domain is preferred. • Hands-on experience writing complex SQL queries, exporting, and importing large amounts of data using utilities. • Ability to build abstracted, modularized reusable code components. • Hands-on experience in generating/parsing XML, JSON documents, and REST API request/responses • Hands-on experience in Redis, Valkey, OpenSearch database • Able to quickly adapt and learn. • Able to jump into an ambiguous situation and take the lead on resolution. • Able to communicate and coordinate across various teams. • Are comfortable tackling new challenges and new ways of working • Are ready to move from traditional methods and adapt into agile ones • Comfortable challenging your peers and leadership team. • Can prove yourself quickly and decisively. • Excellent communication skills and Good Customer Centricity. • Strong Target & High Solution Orientation.