Azure Data Engineer

You will be working on the latest data platform technologies, and a part of a high-performing team fully committed to employee growth and development. If you re a skilled engineer who wants to build using the latest technology and acquire new skills in data and analytics, then come join our team.
You will be integrating components, designing frameworks, and building reusable data solutions for Haleon s Enterprise Data Analytics Platform. You will enable faster acquisition, ingestion, and curation of analytical-ready datasets.

This is very hands-on development role which includes developing delivering code through from origin to production, ensure that code comes in on time, to quality and in line with the overall ecosystem being established.

The Data Engineer will directly contribute to the extensive and varied build and deployment activities involved in establishing the new platform then continue to work on the already significant and growing pipeline of future buildouts of platform services on the Enterprise Data Analytics Platform.

Key responsibilities
Development
Hands on, sleeves up development and delivery expected as a matter of course.

Technical Architecture
Be conversant with technical architecture to contribute to design discussions in partnership with the Delivery/Development Lead and dedicated Analytics Data Architect.

Quality, Risk Compliance:
Ensure all risk and issues associated with owned projects are recorded and managed in the appropriate Risk Issue logs in a timely manner.

Ownership
Take ownership for the delivery/development projects and help steer until completion

Qualifications and skills

4 to 8 years of experience in Data engineering and coding experience in the languages: PySpark, SQL, Spark etc.
Experience with the Azure data and analytics stack: Databricks, Data Factory, SQL DW, etc.
Seasoned coder and problem solver on big-data processing approaches and schema-on-read methodologies. Preference for deep understanding of Spark, Databricks and Delta Lake, and applying them to solve data science and machine learning business problems.
Familiar deploying enterprise analytics solutions at scale with applicable services: administration, qualification, and user access provisioning.
Experience with Agile delivery frameworks and tools: SAFe, Jira, Confluence, Azure DevOps, etc.
Experience with visualization tools and their application: developing reports, dashboards and KPI scorecards.
Experience integrating and supporting a variety of enterprise data tools: Ataccama, Talend, Collibra, Snowflake, StreamSets, etc.
Experience articulating business value of analytics projects and progressing solutions from MVP to scaled-up production solutions.
Ability to work in close partnership with groups across the IT organization (security, compliance, infrastructure, etc.) and business stakeholders in the commercial organizations.
MS/BS degree in Computer Science, Engineering, Data Science or equivalent experience, with preference on experience and proven track record. Ideal candidate would have an impressive hands-on work history in an advanced, recognized, and innovative environment.
Ideal candidate possesses great communication skills and the ability to communicate inherently complicated technical concepts to non-technical stakeholders of all levels.