Senior Data Analytics Manager

Entity:

Technology

Job Family Group:

IT&S Group

Job Description:

Our purpose is to deliver energy to the world, today and tomorrow. For over 100 years, bp has focused on discovering, developing, and producing oil and gas in the nations where we operate. We are one of the few companies globally that can provide governments and customers with an integrated energy offering. Delivering our strategy sustainably is fundamental to achieving our ambition to be a net zero company by 2050 or sooner.

It's an exciting time to join bp. Meeting the energy challenge requires many different approaches and solutions. And as part of Finance Business & Technology (FBT), you’ll be fully connected into the world of bp. You’ll play an increasingly important part within a network of like-minded colleagues partnering on strategic projects that stretch across the globe. And it starts with you. There’s a world of opportunities to build new skills, challenge yourself and grow a long-term career at bp. And no matter where you work, your role will have meaning, purpose and impact. So if you want to be part of a caring, supportive environment where you can realize your full potential, we’re with you.

Join our Team and advance your career as a Senior Data Analytics Manager

A Data Analytics Manager bridges the gap between data engineering, analytics and business delivery, ensuring that data structures, quality processes and reusable data assets support both operational reporting and advanced analytics.

This role combines hands-on technical work with team leadership, building and maintaining robust, scalable and efficient data models that enable trusted, high-quality data use across the organization. Working closely with data engineers, analysts, data scientists and business partners, the role translates business and analytical needs into effective data models, reusable datasets and practical data solutions. It also drives data integrity, accessibility and usability through strong data quality management, governance compliance and continuous improvement of data workflows. Alongside this, the role leads and grows a team, setting clear expectations, coaching others and raising standards across delivery.

In this role You will:

As part of a cross-disciplinary team, working closely with business partners, other data managers, product managers, data engineers, data analysts, data scientists and software engineers, you will:

• Set data standards, co-design data schemas, and ensure quality at source.

• Use your data domain knowledge and business understanding to improve data sources, data products and analytical outputs.

• Work with business partners to coordinate remediation plans so that datasets and data products are fit for purpose at business entity level.

• Cleanse, transform, reconcile and standardize data by creating new or modifying existing scripts and automation.

• See opportunities to automate manual processes and collaborate with data engineers to improve data ingestion, integration, transformation and quality control.

• Support the creation and maintenance of trusted, reusable datasets and curated data assets that can be used across reporting, analytics and data science use cases.

• Partner with analysts and data scientists to understand requirements and help translate them into scalable data models and analytical solutions.

• Contribute to advanced analytics use cases by ensuring data is accessible, reliable and structured appropriately for analysis.

• Define, maintain and improve data quality checks, test validation and sign-off processes.

• Adhere to and advocate for data management and analytics standards.

• Present findings and recommendations to peers and senior partners, influencing decision making where appropriate.

• Mentor, coach and develop others, creating space for the team to grow in capability and impact.

What You will need to be successful:

• Master’s degree in computer science or related field, or equivalent knowledge and experience

• Experience leading, growing and developing a data or analytics team of min. 3–4 people

• Strong hands-on experience in data management, data governance, analytics support and process automation in complex, global environments

• Hands-on knowledge of data management and governance across all data lifecycle stages

• Solid understanding of data models, reusable data assets, data standards and data processes

• Experience working with analysts and data scientists to support reporting, analytics and advanced analytics use cases

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