Head Of Data Engineering

About us

At National Grid, we keep the lights on and homes warm.  But it’s so much more than that.  We keep people connected and society moving.  This is no easy feat, and it takes all of us.  But National Grid supplies us with the environment to make it happen.  As we generate momentum in the energy transition for all, we don’t plan on leaving any of our customers in the dark.  So, join us and help bring energy to life.

Job Purpose

Head of Data Engineering role will be part of the Chief Data Office function and reports into our Chief Data officer and managing team of Data engineers. It is a critical role to deliver on National Grid vision which is "To be at the heart of a clean, fair and affordable energy future". He / she will be working as part of a multi-disciplinary team of Data and analytics leaders, and fellow data engineers to develop and manage data products that can empower our business to make decisions from data to drive growth activities and bring efficiencies to our data processes and data maturity.

He / She will play a pivotal role in operationalizing the most-urgent data and analytics initiatives for Nationalgrid digital business initiatives. The bulk of the activities would be in building, managing and optimizing data pipelines and then moving these data pipelines effectively into production for key business domains, and enterprise initiatives.

Key Accountabilities

•    Guarantee compliance with data governance and data security requirements while creating, improving, and operationalizing these integrated and reusable data pipelines & data products. This would enable faster data access, integrated data reuse and vastly improved time-to-solution for Nationalgrid data and analytics initiatives.

•    This role will require both creative and collaborative working with IT and the wider business. It will involve evangelizing effective data management practices and promoting better understanding of Data and analytics. The position will also be tasked with working with key business stakeholders, IT experts and subject-matter experts to plan and deliver optimal analytics and data science solutions

•    When moving the data, ensure an appropriate level of Data quality is managed. Liaise with stakeholders in building trust in the data being used for decision making. Focus on validation, reconciliation, and automated testing applied end to end.

•    Promote data governance activities to exercise of authority and control of the data. In large scale data pipelines, the need for data governance goes from being a nice-to-have, to be a critical success factor. 

•    Work with Platform engineering teams to drive automation through effective metadata management leveraging well supported Data platforms managed by Platform engineering, He / She will be responsible for using innovative and modern tools, techniques, and architectures to automate the most-common, repeatable, and tedious data preparation and integration tasks partially or completely in order to minimize manual and error-prone processes and improve productivity. 

•    Works closely with Platform engineering to assist with renovating the data management infrastructure to drive automation in data integration and management.

•    Effectively promote data products approach within the enterprise. Support and deliver product centric approach within the enterprise driving innovation at scale.

•    Prepare architectural patterns, guardrails, and best practices related to Data engineering. Consult about current / future industry trends and technology needs.

•    Ensure alignment with Enterprise strategies, aligning the technologies and best practices with those of the enterprise as a whole and clearly document the implications of trade-offs being met

•    Ensures that all business units work with Data Engineering resource to meet their business outcomes by understanding their objectives and formulating demand plans then allocating resources appropriately. 

Supervisory/Interpersonal- Experience Required

•    Strong experience building, managing and working with cross-functional teams in a dynamic business environment.
•    Required to be highly creative and collaborative. An ideal candidate would be expected to collaborate with both the business and IT teams to define the business problem, refine the requirements, and design and develop data deliverables accordingly. The successful candidate will also be required to have regular discussions with data consumers on optimally refining the data pipelines developed in non-production environments and deploying them in production.
•    Required to have the accessibility and ability to interface with, and gain the respect of, stakeholders at all levels and roles within the company.
•    Is a confident, energetic self-starter, with strong interpersonal skills.
•    Has good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.

Technical Skills

    Knowledge 

•    Object-oriented/object function scripting using languages such as [R, Python, Java, C++, Scala, others]

•    Integrate large Heterogeneous datasets. 
o    ETL/ELT
o    Data replication/CDC
o    Message-oriented data movement
o    API design and access
o    Data virtualization

•    Stream Data Integration
o    Open-source & commercial message queuing technologies [such as Kafka, JMS, Azure Service Bus others]
o    Stream data integration technologies such as [Apache Kafka Streams, others]
o    Stream analytics technologies such as [Apache Kafka KSQL, Spark Streaming and, others]

•    Popular open-source and commercial data science platforms such as [Python, R, KNIME, Alteryx, others]

Strong Experience

•    Manage – Design & build data pipelines for data structures

•    Work with both IT and business in integrating analytics and data science output into business processes and workflows

•    Database programming languages 
o    [SQL, PL/SQL, others] for relational databases
o    NoSQL/Hadoop oriented databases like MongoDB, Cassandra, others] for nonrelational databases.

•    Integrating analytics and data science output into business processes and workflows

•    Publishing & governing Data products in Data marketplace

•    Data discovery, analytics and BI software tools like [Tableau, Qlik, PowerBI and others] for semantic-layer-based data discovery.

•    Working with data science teams, helping them to refining and optimizing data science and machine learning models and algorithms.

•    Working with data governance/data quality and data security teams and specifically privacy and security officers in moving data pipelines into production

•    Containerization techniques such as Docker, Kubernetes, and others.

•    Agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse and automation of Data flows between data custodians and consumers across an organization

Metrics for Evaluation

•    On-time and on-scope delivery of Data pipelines / data products in alignment with the business and/or data and analytics and/or data science team(s).
•    Ongoing support of production service-level metrics across production data pipelines.
•    Ability to network and be recognized as a data expert across a variety of business and IT roles.
•    Effectiveness in evangelizing and educating on data issues as measured by the delivery of dedicated internal sessions to various audiences.

Education & Training

•    A bachelor's or master's degree in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field is required.
•    An advanced degree in computer science (MS), statistics, applied mathematics (Ph.D.), information science (MIS), data management, is preferred.
•    The ideal candidate will have a combination of IT skills, data governance skills, analytics 

Previous Experience

•    At least TEN years or more of work experience in data management disciplines including data integration, modeling, optimization, and data quality, and/or other areas directly relevant to Data Engineering responsibilities and tasks.
•    At least FIVE years of experience working in cross-functional teams and collaborating with business stakeholders in UTILITIES in support of a departmental and/or multi-departmental data management and analytics initiative.
•    Preferred FIVE Years of experience within Energy / Utilities sector.
 

More Information

Candidates must be based or be open to relocating to MA, NY, NJ, NH, CT, RI, ME, VT or PA. For Candidates within these States, it’s a hybrid role i.e., occasional travel to our corporate hub.

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