Senior Data Consultant

The Role

We’re looking for a Senior Data Consultant to lead the design and implementation of cloud-native data platforms and pipelines for our clients. You’ll work closely with data architects, analysts, and business stakeholders to deliver robust, scalable, and secure data solutions that meet real business needs.

You’ll be a trusted advisor in client engagements, contributing your technical expertise while mentoring junior team members and promoting best practices in engineering, testing, and automation.

Key Responsibilities

You will be reporting to the Head of Customer Delivery and have the following primary responsibilities:

• Design and implement modern data architectures (e.g. lakehouse, data mesh, event-driven) on cloud platforms such as AWS, Azure, or GCP.
• Build scalable and efficient data pipelines using tools like dbt, Spark, Airflow, or native cloud services.
• Support data ingestion, transformation, and orchestration from multiple structured and unstructured sources.
• Apply strong DevOps/DataOps principles: CI/CD, version control, automation, and monitoring.
• Ensure data quality, lineage, security, and governance are embedded in all engineering outputs.
• Engage directly with clients to understand requirements, present solutions, and deliver outcomes.
• Mentor data engineers and contribute to internal knowledge sharing, frameworks, and standards.

About You

You’re a confident and collaborative data engineer with consulting experience, comfortable working in fast-paced environments and solving complex challenges. You bring deep technical knowledge, a willingness to learn, and a genuine interest in enabling better decision-making through trusted data.

Required Skills & Experience

The ideal candidate will have the following skills and experience:

• 10+ years of experience in data engineering, ideally in consulting or client-facing roles.
• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science or a related field.
• Proven expertise in SQL, Python, and modern data transformation and orchestration solutions such as dbt, Coalesce, Apache Airflow, Prefect.
• Experience designing and implementing cloud-based data platforms (e.g. AWS Redshift, Microsoft Fabric, Snowflake, Databricks, BigQuery).
• Experience designing and implementing modern reporting and business intelligence tools (e.g. Power BI, Tableau).
• Strong understanding of data modelling, data warehousing, and ELT best practices.
• Familiarity with data governance principles (e.g. lineage, cataloguing, masking, governance framework).
• Experience working in Agile or product delivery teams.
• Excellent communication skills and stakeholder engagement abilities.

Bonus Points

The following are not mandatory but would be viewed favourably.

• Certifications in AWS, Azure, GCP, Databricks, MS Fabric, Snowflake, dbt, Tableau, or Power BI.
• Experience with infrastructure-as-code (e.g. Terraform, CloudFormation).
• Exposure to AI/ML data pipelines or real-time streaming architectures.
• Exposure to WhereScape Red.