Data Engineer

Job Description:

Our client is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. We are looking for Data Engineers who will be responsible for designing, building, and maintaining the data architecture and infrastructure necessary for effective data processing and analysis. This role involves collaborating with data analysts, and other stakeholders to ensure that data is accessible, reliable, and optimized for use in various 6 - 12yrs

Work Mode: 4 days WFO & 1-day WFH

Skills: Azure Environment, Data Bricks, ETL tools like SSIS / SSRS etc.

Key Responsibilities:

- 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.

Eligibility Requirements:

- Proven engineering expertise (7 - 10 years).

- Experience with Azure data services such as Data Factory, Databricks, MS Fabric, Synapse Analytics, and ADLS Gen2.

- Experience with source control, CI/CD pipelines, and Azure DevOps.

- Ability to design and deploy Infrastructure as Code (IaC) pipelines.

- Familiarity with modern data architecture including Lakehouse and Medallion architecture.

- Extensive hands-on experience with SQL Server and SSIS.

- Strong understanding of data warehouse modelling, especially Star and Snowflake schemas.

(ref:hirist.tech)