Data Engineer

About the RoleWe are seeking a motivated and technically versatileData Engineer to join our team. You will play a key role in delivering data platforms, pipelines, and ML enablement within a Databricks on Azure environment.As part of a stream-aligned delivery team, you’ll work closely with Data Scientists, Architects, and Product Managers to build scalable, high-quality data solutions for clients. You'll be empowered by a collaborative environment that values continuous learning, Agile best practices, and technical excellence.Ideal candidates have strong hands-on experience in Databricks, Python, ADF and are comfortable in fast-paced, client-facing consultingengagements.Skills and Experience requirements1. TechnicalDatabricks (or similar) e.g. Notebooks (Python, SQL), Delta Lake, job scheduling, clusters, and workspace management, Unity Catalog, access control awarenessCloud data engineering – ideally Azure, including storage (e.g., ADLS, S3, ADLS), compute, and secrets managementDevelopment languages such as Python, SQL, C#, javascript etc. especially data ingestion, cleaning, and transformationETL / ELT – including structured logging, error handling, reprocessing strategies, APIs, flat files, databases, message queues, event streaming, event sourcing etc.Automated testing (ideally TDD), pairing/mobbing. Trunk Based Development, Continuous Deployment and Infrastructure-as-Code (Terraform)Git and CI/CD for notebooks, data pipelines, and deployments 2. Integration & Data HandlingExperienced in delivering platforms for clients – including file transfer, APIS (REST etc.), SQL/NoSQL/graph databases, JSON, CSV, XML, Parquet etcData validation and profiling - assess incoming data quality. Cope with schema drift, deduplication, and reconciliationTesting and monitoring pipelines: Unit tests for transformations, data checks, and pipeline observability 3. WorkingStyleComfortable leveraging the best of lean, agile and waterfall approaches. Can contribute to planning, estimation, and documentation, but also collaborative daily re-prioritisationAble to explain technical decisions to teammates or clientsDocuments decisions and keeps stakeholders informedComfortable seeking support from other teams for Product, Databricks, Data architectureHappy to collaborate with Data Science team on complex subsystemsNice-to-havesMLflow or light MLOps experience (for the data science touchpoints)Dbt / dagster / airflow or similar transformation toolsUnderstanding of security and compliance (esp. around client data)Past experience in consulting or client-facing rolesCandidate Requirements5–8 years (minimum 3–4 years hands-on with cloud/data engineering, 1–2 years in Databricks/Azure, and team/project leadership exposure)Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, Information Systems, Data EngineeringDisclaimer:This job posting is not open to recruitment agencies. Any candidate profile submitted by a recruitment agency will be considered as being received directly from an applicant. Contango reserves the rights to contact the candidate directly, without incurring any obligations or liabilities for payment of any fees to the recruitment agency.#J-18808-Ljbffr