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You will be updated with latest job alerts via emailPosition Title: Data Engineer
Position Type: Regular - Full-Time
Position Location: Gurgaon
Requisition ID:37277
Position Summary
Data engineers are mainly responsible for designing building managing and operationalizing data pipelines to support key data and analytics use cases. They play a crucial role in constructing and maintaining a modern scalable data platform that utilizes the full capabilities of a Lakehouse Platform.
You will be a key contributor to our data-driven organization playing a vital role in both building a modern data platform and maintaining our Enterprise Data Warehouse (EDW). You will leverage your expertise in the Lakehouse Platform to design develop and deploy scalable data pipelines using modern and evolving technologies. Simultaneously you will take ownership of the EDW architecture ensuring its performance scalability and alignment with evolving business needs. Your responsibilities will encompass the full data lifecycle from ingestion and transformation to delivery of high-quality datasets that empower analytics and decision-making.
Duties and responsibilities
Build data pipelines using Azure Databricks:
Drive Automation:
Enterprise Data Warehouse (EDW) Management:
Educate and train:The data engineer should be curious and knowledgeable about new data initiatives and how to address them. This includes applying their data and/or domain understanding in addressing new data requirements. They will also be responsible for proposing appropriate (and innovative) data ingestion preparation integration and operationalization techniques in addressing these data requirements. The data engineer will be required to train counterparts in these data pipelining and preparation techniques.
Ensure compliance with data governance and security:The data engineer is responsible for ensuring that the data sets provided to users are compliant with established governance and security policies. Data engineers should work with data governance and data security teams while creating new and maintaining existing data pipelines to guarantee alignment and compliance.
Qualifications
Education
Bachelor or masters in computer science Information Management Software Engineering or equivalent work experience.
Work Experience
At least four years or more of working in data management disciplines including: data integration modeling optimization and data quality and/or other areas directly relevant to data engineering responsibilities and tasks.
At least three years of experience working in cross-functional teams and collaborating with business stakeholders in support of a departmental and/or multi-departmental data management and analytics initiative.
Technical knowledge Abilities and skills
Ability to design build and manage data pipelines for data structures encompassing data transformation data models schemas metadata and workload management. The ability to work with both IT and business in integrating analytics and data science output into business processes and workflows.
Strong knowledge of database programming languages and hands on experience with any RDBMS.
McCain Foods is an equal opportunity employer. As a global family-owned company we strive to be the employer of choice in the diverse communities around the world in which we live and work. We recognize that inclusion drives our creativity resilience and success and makes our business qualified applicants will receive consideration for employment without regard to race religion color national origin sex age veteran status disability or any other protected characteristic under applicable law.
McCain is an accessible employer. If you require an accommodation throughout the recruitment process (including alternate formats of materials or accessible meeting rooms) please let us knowand we will work with you to find appropriate solutions.
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Job Family:Information Technology
Division:Global Digital Technology
Department:Global Data and Analytics
Location(s): IN - India : Haryana : Gurgaon
Company:McCain Foods(India) P Ltd
Full Time