Sr Manager - Data Engineering

Key Skills

Amazon Athena, Amazon Elastic Compute Cloud-EC2, Amazon EMR, Amazon Simple Storage Service (S3), Apache Kafka, AWS, AWS Glue, Cloud computing, Continuous Integration & Continuous Delivery - CI/CD, Data Biuld Tool - dbt, Data pipelines, Data science techniques, Git, Jenkins, Large data sets, Linux Operating system, NoSQL, Parquet, PowerBI, PySpark, RDBMS, SAP, Scala Programming, Snowflake, Spark Core, Tableau, Terraform, Unix Operating system

Job Description

As a Sr Manager – Data Engineering, you will be a hands-on technical leader who designs and delivers data platform, Lake house and Big Data Solution for Diabetes operating unit. You will execute long term Data strategy and bring extensive experience in both, technical delivery on data and a strong customer-centric approach to product development.

Our mission drives the need to be a highly skilled, flexible, extremely efficient, versatile, and agile in software product development for the benefit of our patients with Type 1 and Type 2 diabetes in need of intensive insulin therapy.

Diabetes impacts over 500 million people around the world — that’s roughly one in 10 adults. That means you probably know someone affected by this disease. At Medtronic, our Diabetes Operating Unit focuses on improving the lives of those within the global diabetes community. As a business, we strive to empower people with diabetes to live life on their terms by delivering innovation that truly matters and providing support in the ways they need it. We’re committed to meeting people with diabetes where they are in their journey, always with an aim to make their lives easier. Our portfolio of innovative solutions is designed to provide customers greater freedom and better health, helping them achieve better glucose control, while spending less time managing their disease.

What you will do:

• Build, schedule, and manage data movement from application origin through batch and streaming systems to make it available for key business decisions. 
• Owing Data access, data observability, Privacy and Data platform security.
• Provide thought leadership on Data management and partner with Data Science, ML engineering, BI and Privacy teams to enable analytics at scale.
• Ensure data products are aligned with the rapidly evolving needs of business.
• Utilize programming languages like Scala, Python and Open-Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Snowflake along with unified data platform like Databricks.
• Design and build highly scalable data pipelines using Spark, Kafka to ingest data from various systems.
• Migrate on-premises/re-design legacy ETL jobs to ELT model, removing dependency from legacy tools. 
• Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies.
• Responsibilities may include the following and other duties may be assigned.

Must Have: Minimum Requirements

• Bachelors degree required
• Minimum of 7 years of relevant experience with 5+ years of managerial experience, or advanced degree with a minimum of 5 years of relevant experience with 5+ years of managerial experience

Nice to Have

• 10 + years of IT experience designing data lakes/big data solutions with bachelor’s in science, engineering, or technical field (or 8 years with masters in STEM) and should have a long history of successfully building and executing on engineering roadmaps, designing, and launching products, and be an expert on modern data engineering. You have strong Data engineering foundation, you are action biased, curious and a self-starter to learn evolving technologies.
• You migrated on premises and cloud-based databases to modern Data platforms using lake house concept with open-source stack.
• You had been a hands-on architect/Sr engineer for 5 years to build Data products using cluster computing on large data sets (minimum 5+ TB data daily), with extensive use of Structured streaming and Kafka on cloud platform (AWS preferred).
• You have built and grown team up to 8 individual contributors on onshore/offshore model.
• 6 years of hands-on experience in designing Spark pipeline with Scala and Pyspark.
• 4+ years in designing Airflow pipelines and deployment in Prod.
• 4+ years of experience in designing CI/CD pipelines either with Jenkins or Git actions.
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Min Salary USD: 142,000.00

Max Salary USD: 213,600.00