Data Engineering Manager

Location: Turkey
Full/part time: Full-time
Level: WL2A/B
Reports to: Data and Analytics Market Lead
Start Date: ASAP

CONTEXT:
Unilever is driving digital transformation deliver 4G growth. Our mission is to transform our organization to a digital first culture, delivered by a world-class data and insights team, leaping ahead of our competition in everything we do.

UL’s D&A Market teams will lead the path for UL to become data-intelligent. The team will do this by delivering advanced products at scale, enabling UL functions, UniOps and leadership teams to turn data into insights, actions and decisions at a faster pace than ever before to achieve competitive edge for UL.

Each Market team consisting of technical (data engineering and science) expertise as well as functional business insight generation expertise (e.g. Finance, CMI, CD) will work with other Market teams and the D&A Global team to ensure that insights discovered locally are joined up and enhanced with regional/globally-discovered or researched insights to enable joined-up recommendations and decisions aimed at driving incremental growth by meeting the needs of our consumers, customers and employees.

With the ULE looking to D&A Market teams to power the exponential growth of UL in an in increasingly VUCA (volatile, uncertain, complex and ambiguous) context, it is imperative that D&A Market teams are organised to be highly adaptive and flexible to demand, fast-changing priorities and emergent opportunities. To do this, it will be important for the D&A Market team to have an agile mindset, org structure and ways of working (beyond agile tools and techniques) – i.e. able to embrace uncertainty, ambiguity, and to create structure out of chaos.

There are five major themes in the Data and Analytics global strategy that will relate to the work of D&A Market teams:

Deliver Intelligent systems at scale. Powering Business (cross functional) and Customer Development area through data and analytics. Building out the right applications to enable business teams to move faster, with more accurate and future looking decisions leveraging Big Data & Data Science.
Winning disproportionately. Creating analytics products that make a significant impact on our business and drive competitive advantage in the market, while collaborating appropriately with other markets and Global teams (i.e. winning both locally and globally for UL).
Drive Unilever to assisted and predictive decision-making. The future is about assisted decision-making with machines (AI/Cognitive Computing/Machine Learning) unlocking the insights from vast deluge of consumer, customer & internal data, and presenting this in a way that is simple for our teams.
Make data a true asset. Better data and data science access for every part of Unilever, across the 3 data framework (Connectivity, Growth, Continuous Improvement) and leading through the Enterprise Data Executive.
World-class Information. One Version of the Facts. Continued excellence in delivery of diagnostics and insights to focus attention when and where it matters with a focus on Big Bets, Strategic Initiatives and Leadership team reporting

TEAM’S RESPONSIBILITIES:
This team is responsible for managing the market’s demand for data, analytics and insights. It will lead data analytics, data warehousing, research development and implementation of appropriate data systems and analytic solutions. It is also responsible for streamlining in-scope processes related to data analytics and insights generation in the market, through automating, consolidating and eliminating them where appropriate to deliver a seamless, fast insights-generation experience using tooling provided by the Global D&A team.

We are looking for a passionate Senior Data Engineer, who enjoys building and optimising data systems. The role works closely with the NAMETRUB D&A Team and Global D&A organisation.

MAIN JOB PURPOSE:
This role will provide technical data leadership in our D&A Market team. You will be responsible for creating, expanding, optimising and managing our data depository warehouse and data pipeline architecture, as well as optimising data flow and collection. This role will support our data initiatives and will ensure optimal data delivery architecture is consistent throughout the organisation and ongoing projects.

Main accountabilities:
Be the expert in UL Data, current and future
Create and maintain optimal data pipeline architecture to balance performance and cost
Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, refactoring current architecture, data governance inc. lineage, catalogue and quality.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Data Warehousing, PySpark/Spark, Python and Cloud technologies.
Work with software engineering best practices such as version control, continuous integration and test-driven development including Azure Dev Ops and Git.
Work with MS Azure including Databricks (Pyspark and Delta Lake), Data Factory, Dev Ops, ADLS, Blob Storage and Power BI Datasets
Use of advanced SQL skills and an understanding of query and storage optimisation
Ensure that deliverables meet or exceed functional, technical and performance requirements
Contribute to the development of your own and team’s technical acumen
Continuous learning of new tools & technologies via external sources that brings direct value to the business

EXPERIENCE, QUALIFICATIONS AND QUALITIES:
Essential

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases
• Experience building and optimising data pipelines, architectures and datasets
• Working knowledge of architectures to support advanced analytics and data science
• Strong analytic skills related to working with unstructured datasets
• Knowledge about and experience of use of data to deliver business insights and transform delivery in an FMCG context
• Experience with building processes supporting data transformation, data structures, dependency and workload management
• A successful history of manipulating, processing and extracting value from large disconnected datasets
• Working knowledge of message queuing, stream processing, and highly scalable data stores
• Experience supporting and working with cross-functional teams in a dynamic environment

Preferred

• Basic knowledge of building advanced and repeatable analytics models that enable the business to make better decisions, drive 4G, and gain competitive advantage
• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• Understanding of end-to-end processes and key cycles from a Market (local) perspective
• Basic experience of leading a team of specialists
• Basic people management skills

Standards of Leadership

• Personal Mastery (Data-science and advanced analytics)
• Agility
• Passion for High Performance
• Business Acumen

Qualifications

• B.S. or M.S in a relevant field (Business Analytics, Operations Research), or PhD, M.S. in a relevant technical field (Operations Research, Computer Science, Statistics, Business Analytics, Econometrics, or Mathematics)
• Overall experience of 2-5+ years in data engineering
• Experience with Azure cloud services (Azure Databricks, Azure Data Factory, Azure DevOps, Azure Analysis Services and ADLS)
• Experience with Power BI (including Dax and M)
• Experience with relational SQL and NoSQL databases
• Proven familiarity with Data Governance processes and managing data quality, access, lineage and profiling using automated testing and continuous integration where relevant.
• Working knowledge of SQL, Python and Spark.
• Natural curiosity and imagination to create novel business solutions

KEY CAPABILITIES:

• Data Expertise
• Machine Learning
• Project Management
• Python
• Agile delivery
• Dashboard development
• Data Warehouses, Data Lakes and Database management
• Data querying, processing and ETL
• Data management principles
• Data modelling
• System and process design
• Coding and testing

KEY INTERFACES:
Internal

• Market LT
• Market D&A Team
• NAMETRUB D&A Team
• Global D&A Team
• Unilever Business leaders and subject matter experts
• Global business topic Subject Matter Experts
• D&A Market Teams across UL

External

• Partner Analytics and Data Organisations / Contractors