Job Location: Poona
As a Data Engineer, you would work closely with domain experts in defining well thought and thorough warehousing solutions. You would be involved in all phases of development like project scoping, team building, working with business leads and project managers, organizing sprints, managing deadlines, understanding, and articulating priorities, architecting solutions, coding, and delivering high quality results. You will be leading all the data engineering pipeline solution. Designing warehouse and envision and execute POC’s for new technologies and mentor other team members in setting up best practices for development.
- Understanding business processes, understanding the software systems for retrieval, prepping and modelling data to build a data warehouse in Snowflake for supporting reports and Dashboards.
- Create and maintain optimal data pipeline architecture.
- Assemble large, complex data sets that meet functional/non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Azure and Snowflake technologies.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with stakeholders including the Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- Working experience in Snowflake data cloud & Data Vault Modelling is a plus and good to have.
- Have thorough knowledge of Data Warehousing designs and have experience in designing conceptual and logical data models.
- Design and Implement ETL solutions end to end using Azure or Snowflake cloud data platforms.
- Should be adept in performance improvement techniques, resulting in cost saving.
- Familiarity with data visualization tools (e.g., PowerBI, Tableau)
- Experience building and optimizing data pipelines, architectures, and data sets.
- Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
- A successful history of manipulating, processing, and extracting value from large, disconnected datasets.
- Knowledge of Agile and Scrum Practices.
BE, MSc, MCA, Computer Science, or related discipline.
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