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About the role
The role involves developing, maintaining, and enhancing data pipelines and ETL/ELT processes within a data warehousing architecture. You will also be responsible for troubleshooting pipeline issues, optimizing SQL queries, and implementing data security measures.
What they look for
Requirements
Candidates must have 5 to 7 years of experience in data engineering with proficiency in IDMC, Snowflake, and SQL. A strong background in big data tools, software development lifecycles, and agile methodologies is required.
Full description
Position: Midlevel- Data Engineer-(IDMC+Snowflake+SQL)
Location: Pune/Hybrid
Experience: Min 5 to 7 Years
- Development, maintenance, and enhancement of Data Pipelines (ETL/ELT) and processes with thorough knowledge of star/snowflake schemas
- Hands on experience in PowerCenter Developer/IDMC/IICS Data Integration
- Experience in DW Production Support / troubleshooting data or pipeline issues
- Developing complex SQL queries and SQL optimization
- Development experience must be full Life Cycle experience including business requirements gathering, data sourcing, testing/data reconciliation, and deployment within Business Intelligence/Data Warehousing Architecture.
- Designing and implementing data security
- Monitoring and optimizing data storage and data processing
- Use of Object function/object-oriented scripting languages including Scala, C++, Java and Python
- Cloud data warehouse and data lake platforms (e.g., Snowflake, Databricks, Redshift, BigQuery, MS Synapse, MS ADLS, Apache Haddop, etc.)
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Understanding of data science concepts
- Familiarity with AI/ML frameworks and libraries
Requirements
- Developing data services that are fit for purpose, resilient, scalable, and future proof, to meet user needs
- Advanced SQL knowledge and experience working with relational databases and working familiarity with various databases.
- Demonstrated understanding and experience using software and tools including ETL, relational SQL and NoSQL databases, big data tools like Kafka, Spark, and Hadoop
- Experience building and optimizing ‘big data’ data pipelines, architecture, and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with unstructured datasets.
- Experience and knowledge of project management best practices and agile software development methodologies
- A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
- Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
- Strong project management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- Understanding of data science concepts
- Familiarity with AI/ML frameworks and libraries
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