Smith+Nephew
SeniorDataEngineer
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optimal for Senior candidates.
“Senior Data Engineer at Smith+Nephew. Skills: Data Engineering, Snowflake, ELT pipelines, SQL. Lead data engineering delivery teams. Design scalable ELT pipelines”
What They're Looking For.
Must Have
BSc degree in IT or related discipline, 6+ years of experience in data engineering or software engineering, at least 4 years in cloud-based data platforms, enterprise data platforms (preferably Snowflake on AWS), ELT tools such as Matillion, Fivetran, or Informatica IICS, Advanced SQL skills, data warehousing concepts, CI/CD pipelines, automated testing, deployment processes, data governance, metadata management, data quality practices
Nice to Have
Cloud certifications (AWS, Snowflake, or equivalent), Python for data engineering and automation, DBT (Data Build Tool), data product thinking, domain-driven data design, BI tools such as Power BI, data platforms supporting AI/ML initiatives
What You'll Do.
Lead data engineering delivery teams
Design scalable ELT pipelines
Ensure solutions align with enterprise data models
Translate requirements into data solutions
Ensure enhancements align with platform standards
Enforce Data Services processes
Implement data orchestration
Optimize Snowflake workloads
Support production environments
Drive adoption of best practices
Coach and mentor engineers
How You'll Work.
Team & Collaboration
Collaborates closely with cloud engineers, product owners, business engagement leads, business analysts, architects, and BI teams; Collaborate with business engagement teams and business analysts; Partner with architecture teams; Coach and mentor engineers across teams
Full Job Description
Role: Senior Data Engineer Location: Kharadi, Pune ## **Life Unlimited.** At Smith+Nephew, we design and manufacture technology that takes the limits off living. Role Profile Overview - Senior Data Engineer (ELT): As a Senior Data Engineer, you play a critical role in the Unified Data Platform (UDP) product lifecycle — from ideation through delivery and continuous optimization — working across multiple delivery pods to ensure scalable, reusable, and governed data solutions. Collaborates closely with cloud engineers, product owners, business engagement leads, business analysts, architects, and BI teams to deliver high-quality, cloud-native data products aligned to enterprise data models and standards. **What will you be doing?** * Lead and coordinate multiple data engineering delivery teams to ensure alignment with Unified Data Platform standards and delivery protocols * Design and develop scalable ELT pipelines to ingest, transform, and publish data into data lakes, data warehouses, and curated data products * Ensure solutions align with enterprise data models, leveraging existing dimensions and fact tables to promote reuse and eliminate redundancy * Collaborate with business engagement teams and business analysts to refine requirements and translate them into scalable data solutions * Partner with architecture teams to ensure new enhancements and data products align with the existing platform and modeling standards * Enforce adherence to Data Services processes, including coding standards, CI/CD pipelines, testing strategies, and deployment protocols * Implement data orchestration, monitoring, and automated quality control processes * Define and manage metadata, lineage, and data governance requirements * Optimize performance of data pipelines and Snowflake workloads * Support production environments and continuous improvement * Drive adoption of best practices in data engineering * Coach and mentor engineers across teams ## **What will you need to be successful?**
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