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

National Grid is hiring a Head of Data Engineering for our Data Office.

The Head of Data Engineering role will be part of the Chief Data Office function and reports into our Chief Data Officer, managing a team of Data Engineers.

It is a critical role to deliver on National Grid's vision which is "To be at the heart of a clean, fair, and affordable energy future".

He / She will work as part of a multi-disciplinary team of data and analytics leaders, and fellow data engineers to develop and manage data products that empower our business to make decisions from data to drive growth activities and bring efficiencies to our data processes and data maturity.

They will play a pivotal role in operationalizing the most urgent data and analytics initiatives for National Grid's 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.

This is a hybrid position and will require candidates to travel to their nearest corporate hub 1x a week. Candidates must be based or be open to relocating to MA, NY, NJ, NH, CT, RI, ME, VT, or PA.

Key Accountabilities

Guarantee compliance with data governance and data security requirements while creating, improving, and operationalizing integrated and reusable data pipelines & data products.

This would enable faster data access, integrated data reuse, and vastly improved time-to-solution for National Grid 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 a 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 authority and control of the data. In large-scale data pipelines, the need for data governance goes from being a nice-to-have to 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.

• Work closely with Platform Engineering to assist with renovating the data management infrastructure to drive automation in data integration and management.
• Effectively promote a data products approach within the enterprise. Support and deliver a 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.
• Ensure that all business units work with data engineering resources 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.

Apply now, read the job details by scrolling down Double check you have the necessary skills before sending an application.

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

• Object-oriented / object function scripting using languages such as R, Python, Java, C++, Scala, others
• Integrate large heterogeneous datasets.
• ETL / ELT
• Data replication / CDC
• Message-oriented data movement
• API design and access
• Data virtualization
• Stream Data Integration
• Open-source & commercial message queuing technologies such as Kafka, JMS, Azure Service Bus others
• Stream data integration technologies such as Apache Kafka Streams, others
• 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
• SQL, PL / SQL, others for relational databases
• NoSQL / Hadoop oriented databases like MongoDB, Cassandra, others for non-relational 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 refine and optimize 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

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Salary

Brooklyn, NY $207,000 - $293,000 a year

Waltham, NY $194,000 - $274,000 a year

Syracuse, NY $173,000 - $244,000 a year

Please be advised that due to the nature of this position, incumbents are subject to federal Drug & Alcohol safety regulations governing US Department of Transportation ("DOT") covered positions, including the Federal Motor Carrier Safety Administration (FMCSA) and Pipeline Hazardous Material Safety Administration (PHMSA).

As such, the Company's testing programs and policies regarding the use of federally prohibited drugs or alcohol, for recreational or medical purposes, will remain in effect for these safety-sensitive, DOT covered positions.

This position has a career path which provides for advancement opportunities within and across bands as you develop and evolve in the position;

gaining experience, expertise and acquiring and applying technical skills. Candidates will be assessed and provided offers against the minimum qualifications of this role and their individual experience.

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