Met Data Engineering Lead
تفاصيل الوظيفة
**Main Job Purpose**:This role will provide technical data leadership of our METR D&A Market teams. You will be responsible for- creating, expanding, optimizing and managing our Analytical stacks with the target of having "data as a consumable product" while keeping in mind correctness, freshness and quality of the data.- building and/or rolling out new D&A products and maintaining existing ones- enabling data initiatives- ensuring optimal data delivery structure is consistent throughout the organization and ongoing projects.**Main Accountabilities**:- Be the main accountable and technical lead for METR and market level holistic data foundation for current and future Data & Analytics Products- Lead the team of data engineers, lead data engineering best practices such as version control, continuous integration and test-driven development including Azure Dev Ops and Git.- Lead your own and team's technical acumen improvement & upskilling, Continuous learning of new tools & technologies via external sources that brings direct value to the business- Lead UL DaaP (Data as a Platform) implementations and processes for METR data foundation and markets' data foundation- Orchestrate all levels of data foundation and data engineering processes- Work with Portfolio Mng, Data CoE, Solution Factory, DL Management and Technical Data Architecture Teams on global level- Work with METR Data architect for METR Data Foundation Strategy & Execution- Work with METR and market data engineers for METR and market data lakes- Generate and enable a holistic data foundation view and roadmap for METR level and for each market depending on market data availability in DaaP (in coordination with global teams) and on market data maturity- Design and lead assembling large, complex data sets that meet functional / non-functional business requirements for METR and METR markets, ensure that deliverables meet or exceed functional, technical and performance requirements- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, refactoring current architecture, data governance inc. lineage, catalogue and quality.- Enable a common way of working for MS Azure, including Databricks, Data Factory, Dev Ops, ADLS, Blob Storage and Power BI Datasets, and usage for advanced SQL skills and an understanding of query and storage optimization- Lead your own and team's technical acumen improvement & upskilling, Continuous learning of new tools & technologies via external sources that brings direct value to the business- Create and maintain optimal Data & Analytics pipeline to balance performance and cost- Enable a single approach and way of working on "Data Governance" for METR and METR markets**Experience and Qualifications***:**Essential**- Technical Skills- Implementing, maintaining and optimizing high-performance APIs, data pipelines and analytic solutions- Hands-on experience working with data architectures and cloud technologies, designing solutions and patterns, and developing projects with them (E2E)- Extracting and dealing with data from multiple data sources, experience with data pipeline and workflow management tools, building and optimizing data pipelines and datasets. Designing extensions to the data lake, data marts, and data integrations to support data-driven projects- Experience building and optimizing data pipelines, architectures and datasets- Having programming proficiency and profound knowledge in SQL, Python and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases- Working knowledge of architectures to support advanced analytics and data science- Cloud environment, preferably with Microsoft Azure (ideal), Google Cloud Platform (GCP) or AWS- Strategic Understanding and Leadership Skills- Balanced profile of functional business knowledge/understanding and data/analytics expertise- People leadership experience & good people management skills with experience of creating and managing effective teams- Great communication and collaboration skills and agile mindset, self-organization as an individual and as a team- Having Agile mindset and experience- Provide coaching and support to transfer technical & data knowledge- Passion for high performance- Process Engineering- Engage with stakeholders to understand the business, problem statement and requirements and communicate to all impacted stakeholders any data quality, timing or definition issues discovered (Global and local, internal and external)- Enable a holistic data foundation view and advocate and influence single version of the truth, end user experience simplification and elegance- Experience with building processes supporting data transformation, data structures, dependency and workload management- A successful history of managing, processing and extracting value from large, disconnected datasets- Experience
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