Job Summary
Senior Data SME - Job Description Experience : 15+ years Experience in all 4 platforms, Business Platform, Technology platform, Enablement platform, Foundation Platform Business Perspective Experience as Principal Arch in leading organizations handling customers effectively. Advanced understanding of Enterprise Architecture principles. Well-versed with the end to end data management philosophies and governance processes fit to business. Deliver data solutions and integration pipelines in accordance with agreed organizational standards that ensure services are resilient, scalable and future-proof Collaborate with cross-functional teams to define and implement cloud strategies that align with business goals Participating in architectural discussions and decision-making processes to ensure alignment with business goals and best practices Working experience on Modern data platforms which involves Cloud & related technologies, Graph databases, Virtualization Technology Perspective Worked in multiple large distributed mission critical applications as an architect. Proven experience as architect and engineering lead in Data & Analytics stream. In-depth understanding of data structure principles and data platforms Used Architecture tools for modelling. Working experience on Modern data platforms which involves Cloud & related technologies Keeps track of industry trends and incorporates new concepts Advanced understanding of AI concepts , LLMS, RAG, Agentic apps Advance Understanding in Data visualization and Data pipelines. Excellent understanding of traditional and distributed computing paradigm. Experience in designing and building scalable data pipelines. Should have excellent knowledge in data warehouse / data lake technology and business intelligence concepts Should have good knowledge in Relational, No-SQL, Big Data Databases and should be able to write complex SQL queries Should have strong implementation experience in all the below technology areas (breadth) and deep technical expertise in some of the below technologies Data integration – ETL tools like IBM DataStage, Talend and Informatica. Ingestion mechanism like Flume & Kafka. Data modelling – Dimensional & transactional modelling using RDBMS, NO-SQL and Big Data technologies. Data visualization – Tools like Tableau Big data – Hadoop eco-system, Distributions like Cloudera / Hortonworks, Pig and HIVE Data processing frameworks – Spark & Spark streaming Hands-on experience with multiple databases like PostgreSQL, Snowflake, Oracle, MS SQL Server, NOSQL (HBase / Cassandra, MongoDB) Experience in cloud data eco-system - AWS, Azure or GCP in the data engineering space with at least few complex & high-volume data projects as an architect is mandatory Contributing to developing and maintaining cloud governance frameworks, policies, and procedures Proficient in integrating cloud services with existing on-premises systems and applications, understanding various integration techniques Enablement & Foundation Perspective Published white papers in recognized forums Knowledgeable in ROI and benefits analysis Very good presentation/Articulation skills Awareness of Security concerns while designing enterprise applications Creative problem-solver with strong communication skills Show an awareness of opportunities for innovation with new tools and uses of
Key Responsibilities
2. Utilize sql for querying and analyzing large datasets in google bigquery.
3. Develop and implement python scripts for automation and data manipulation tasks.
4. Create and optimize data processing pipelines using google dataflow.
5. Collaborate with stakeholders to understand data modeling requirements and utilize ca erwin data modeler for effective data modeling.
6. Monitor data quality, troubleshoot issues, and ensure data integrity across systems.
7. Stay updated with the latest technological advancements in data analytics and contribute to process improvements.
Skill Requirements
2. Strong command over sql for querying and analyzing datasets.
3. Advanced knowledge of python programming for data manipulation and automation.
4. Experience with google dataflow for building and optimizing data pipelines.
5. Familiarity with ca erwin data modeler for effective data modeling and database design.
6. Strong analytical and problem-solving skills to handle complex data related challenges.
7. Excellent communication skills to collaborate with cross functional teams and stakeholders effectively.
8. Ability to work in a fast paced environment and manage multiple priorities simultaneously.