Data Platform Expert developing and maintaining data solutions for analysis and reporting at Magna Electronics. Collaborating with various teams to enhance data - driven decision making and insights.
About the role
- Data Engineer creating advanced data solutions for Mastercard, a global payments technology company. Collaborate cross-functionally to implement robust data pipelines and architectures.
Responsibilities
- Gather and understand the data engineering requirements based on the product and Engineering specifications
- Conduct data discovery to build data models, schemas, tables, view, schemas deployment and many more
- Building appropriate data pipelines in the application to support ETL and automate the pipelines
- Build or use existing tools to execute one time ad-hoc data engineering asks
- Implement and manage CI/CD pipelines using GitLab and Jenkins, enabling automated testing, deployment, and monitoring of data workflows
- Build fact tables, conduct analysis and reporting as per needs
- Conduct data analysis and perform data operations to support business decisions
- Provide architecture guidelines and support from Data engineering aspects in product development
- Apply exceptional problem-solving and analytical skills to troubleshoot complex data and system issues
- Support Data Science team in building model deployment, data pipelines, serving etc
- Document pipeline architecture, processes, and standards, promoting consistency and transparency across the team
- Learn latest trends in data engineering concepts, tools and share with wider organization in brown bags etc
- Provide thought leadership within this area for the entire department
- Work with TPMs, product and relevant stakeholders while executing Data engineering assignments by leading the plan
Requirements
- Expert in SQL development with hands-on experience in Databricks, Snowflake, Python, and PySpark for designing and implementing advanced data engineering solutions
- Proven experience collaborating with stakeholders and cross-functional teams to understand business requirements and deliver reliable, high-impact cloud data solutions across Azure, AWS, and Cloud Data Warehouse platforms
- Strong leadership and communication skills, with the ability to guide and mentor data engineering teams, ensuring effective collaboration between technical and non-technical stakeholders
- Skilled in architecting and developing scalable, reusable data models, pipelines, and frameworks leveraging Hadoop, NiFi, and modern cloud Data Lake architectures
- Experienced in planning and executing end-to-end deployments, upgrades, and migrations with minimal disruption to operations, ensuring adherence to best practices in cloud-native and distributed systems
- Holds a Bachelor’s degree in Computer Science
- Good understanding of payment networks
- Skill in identifying new product ideas from data
- Experience publishing and protecting scientific intellectual property work
Benefits
- insurance (including medical, prescription drug, dental, vision, disability, life insurance)
- flexible spending account and health savings account
- paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave)
- 80 hours of Paid Sick and Safe Time
- 25 days of vacation time and 5 personal days, pro-rated based on date of hire
- 10 annual paid U.S. observed holidays
- 401k with a best-in-class company match
- deferred compensation for eligible roles
- fitness reimbursement or on-site fitness facilities
- eligibility for tuition reimbursement
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