
Data Engineering Specialist
- Mumbai, Maharashtra
- Permanent
- Full-time
- Work closely with end-users and Data Analysts to understand the business and their data requirements.
- Carry out ad hoc data analysis and transform data using Databricks, MS Fabric, or Synapse Analytics.
- Building meta-data driven data ingestion patterns using Azure Data Factory and Databricks, or MS Fabric, or Synapse
- Build and maintain the on-premises SQL Data Warehouse.
- Build and maintain business focused data products.
- Build and maintain Azure Analysis Services cubes.
- Work with Architecture and Engineering teams to deliver projects, and ensure that supporting code and infrastructure follows best practices outlined by these teams.
- Collaborate with Data Engineering Lead, Data Domain Lead and Architect to drive group engineering context within the team continuously.
- Develop and promote exceptional engineering documentation and practices.
- Actively engage with the business units engineering community to promote knowledge sharing.
- Collaborate with squad leader, Head of, engineers, and architects to ensure cohesive strategies and practices within the team.
- Actively encourages creating Investec open-source software where appropriate within the business unit.
- Actively encourages team members within the business unit to speak at technical conferences based on the work being done.
- Excellent data analysis and exploration using T-SQL
- Strong SQL programming (stored procedures, functions)
- Extensive experience with SQL Server and SSIS
- Knowledge and experience of data warehouse modelling methodologies, in particular Star Schema and Snowflake Schema
- Experience in Azure - one or more of the following: Data Factory, Databricks, MS Fabric, Synapse Analytics, ADLS Gen2.
- Experience in building robust and performant ETL processes.
- Experience in using source control, CI/CD pipelines, and Azure DevOps.
- Build 'infrastructure-as-code' deployment pipelines.
- Familiarity with modern engineering practices and data store design, in particular Lakehouse and Medallion architecture.
- Familiarity with the Data as a Product approach
- Excellent analytical and problem-solving skills, with the ability to think critically and strategically.
- Strong communication and interpersonal skills, with the ability to engage and influence stakeholders at all levels.
- To always act with integrity and embrace the philosophy of treating our customers fairly.
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