Job Description We are seeking a Data Consultant to join a high-impact project for a based private debt investment client. The role focuses on designing and implementing scalable data pipelines, data models, and migration processes using Snowflake and modern data transformation tools (Coalesce.io / dbt). This position requires a high level of autonomy, ownership, and proactive mindset, working closely with business stakeholders to translate requirements into robust data solutions. As a Data Consultant at Endava you will focus on the technical implementation of various data projects, from designing and building DW solutions, to developing end to end migration frameworks or building data reporting systems. Key Responsibilities Design, build, and optimize data pipelines and transformations Translate business requirements into technical data models and pipelines . Embed data quality rules and validation checks within pipelines and data models. Provide technical guidance on Snowflake, Coalesce, and Fivetran usage and trade-offs. Ensure data governance, lineage, and metadata management using tools like Alation. Contribute to CI/CD processes , Azure devops, enabling automated deployments across environments. Define and enforce data engineering standards (naming conventions, metadata, tagging, DQ frameworks). Required Technical Skills Strong expertise in SQL (advanced level). Hands‑on experience with Snowflake . Experience with data transformation tools : Coalesce.io or dbt (Data Build Tool). Experience building ETL/ELT pipelines and data migration solutions. Knowledge of data modeling techniques Data Vault / Kimball (dimensional modeling). Experience working with CDC pipelines and large datasets (e.g., SQL Server CDC, ADF). Understanding of CI/CD practices in data engineering. Required Soft Skills Strong autonomy and self‑management (critical for success in this role). High level of initiative and proactivity . Excellent analytical and problem‑solving skills . Ability to translate business needs into technical solutions . Strong communication skills for stakeholder interaction. Nice to Have Experience in banking, asset management, or capital markets . Knowledge of data governance frameworks and enterprise data standards . Familiarity with data governance and lineage tools (e.g., Alation is a plus). Key Success Factors Ability to own and deliver data engineering solutions autonomously . Strong business understanding and requirement translation capability. Commitment to data quality, governance, and scalability . Experience working in a fast‑paced, high‑impact financial environment . Qualifications Programming Languages: Python, Scala, SQL Big Data Frameworks: Apache Spark, Databricks (including Delta Lake and Delta Tables) Cloud Platforms & Services: Microsoft Azure (Azure Data Factory, Azure Event Hub, Azure Functions) Data Engineering: Data pipelines, ETL/ELT design, batch and streaming data processing Data Storage & Management: Delta Tables, Azure Data Lake, Azure Blob Storage Orchestration & Integration: Azure Data Factory (ADF), Azure Functions, Event‑driven architecture Workflow & Automation Tools: CI/CD pipelines, version control (Git), DevOps practices Data Modeling & Warehousing: Dimensional modeling, data lakes, lakehouse #J-18808-Ljbffr