Data Engineering Consultant

Technology is our how. And people are our why. For over two decades, we have been harnessing technology to drive meaningful change.

By combining world-class engineering, industry expertise and a people-centric mindset, we consult and partner with leading brands from various industries to create dynamic platforms and intelligent digital experiences that drive innovation and transform businesses.

From prototype to real-world impact – be part of a global shift by doing work that matters.

Role Overview

A Data Engineering Consultant designs, implements, and optimizes scalable data pipelines and architectures. This role bridges raw data and actionable insights, ensuring robustness, performance, and data governance. Collaboration with analysts and scientists is central to delivering high-quality solutions aligned with business objectives.

Key Responsibilities

• Data Pipeline Development

• Architect, implement and maintain real-time and batch data pipelines to handle large datasets efficiently.
• Employ frameworks such as Apache Spark, Databricks, Snowflake or Airflow to automate ingestion, transformation, and delivery.

• Data Integration & Transformation

• Work with Data Analysts to understand source-to-target mappings and quality requirements.
• Build ETL/ELT workflows, validation checks, and cleaning steps for data reliability.

• Automation & Process Optimization

• Automate data reconciliation, metadata management, and error-handling procedures.
• Continuously refine pipeline performance, scalability, and cost-efficiency.

• Collaboration & Leadership

• Coordinate with Data Scientists, Data Architects, and Analysts to ensure alignment with business goals.
• Mentor junior engineers and enforce best practices (version control, CI/CD for data pipelines).
• Participate in technical presales activities and client engagement initiatives.

• Governance & Compliance

• Apply robust security measures (RBAC, encryption) and ensure regulatory compliance (GDPR).
• Document data lineage and recommend improvements for data ownership and stewardship.

• Programming: Python, SQL, Scala, Java.
• Big Data: Apache Spark, Hadoop, Databricks, Snowflake, etc.
• Cloud: AWS (Glue, Redshift), Azure (Synapse, Data Factory, Fabric), GCP (BigQuery, Dataflow).
• Data Modelling & Storage: Relational (PostgreSQL, SQL Server), NoSQL (MongoDB, Cassandra), Dimensional modelling.
• DevOps & Automation: Docker, Kubernetes, Terraform, CI/CD pipelines for data flows.

• Architectural Competencies

• Data Modelling: Designing dimensional, relational, and hierarchical data models.
• Scalability & Performance: Building fault-tolerant, highly available data architectures.
• Security & Compliance: Enforcing role-based access control (RBAC), encryption, and auditing.

Discover some of the global benefits that empower our people to become the best version of themselves:

• Finance: Competitive salary package, share plan, company performance bonuses, value-based recognition awards, referral bonus;
• Career Development: Career coaching, global career opportunities, non-linear career paths, internal development programmes for management and technical leadership;
• Learning Opportunities: Complex projects, rotations, internal tech communities, training, certifications, coaching, online learning platforms subscriptions, pass-it-on sessions, workshops, conferences;
• Work-Life Balance: Hybrid work and flexible working hours, employee assistance programme;
• Health: Global internal wellbeing programme, access to wellbeing apps;
• Community: Global internal tech communities, hobby clubs and interest groups, inclusion and diversity programmes, events and celebrations.

Our diversity makes us stronger – it drives meaningful change and enables us to build innovative technology solutions. We are committed to creating an inclusive community where all of us, regardless of background, identity, or personal characteristics, feels valued, respected, and free from discrimination. As an equal opportunity employer, we welcome applications from all individuals and base hiring decisions on merit, skills, qualifications, and potential.

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