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Eaglecliff Recruitment

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Senior Data Engineer: Databricks & Delta

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Summary

Contract role designing scalable data pipelines on Databricks and Delta Lake for an energy trading company in London — building real-time streaming analytics, ingesting SAP data via Qlik Replicate and ADF, and optimizing data models on Azure for reporting and decision-making.

Overview

In this role you will design and implement scalable data pipelines and enable real-time and batch analytics for a leading energy trading company. You will work with cross-functional teams to build robust data solutions that support decision-making and reporting at scale. The position focuses on Databricks, Delta Lake, streaming architectures, and SAP data ingestion, offering an opportunity to impact data-driven decisions across the organization. This contract role combines hands-on engineering with shaping data platforms to support energy trading operations.

Responsibilities

  • Design and implement scalable data pipelines using Databricks and Delta Live Tables (DLT)
  • Develop and manage streaming data solutions for real-time analytics
  • Ingest data from SAP systems using Qlik Replicate and ADF to ensure data quality
  • Perform data modelling and optimize data structures for analytics and reporting
  • Collaborate with cross-functional teams to understand data requirements and deliver robust solutions
  • Monitor, troubleshoot, and enhance data workflows for performance and reliability
  • Maintain technical documentation and contribute to data engineering best practices

Key requirements
  • Strong experience with Databricks- DLT, Delta Lake concepts, UC governance
  • Solid understanding of streaming technologies (e.g., Spark Structured Streaming, Autoloader)
  • Programming skills in Python, SQL, or Scala
  • Proficiency in data modelling, ETL/ELT processes, and data architecture
  • Experience in MS Copilot, AI Foundry, Databricks (MosiacAI, MLflow, Agentbricks, Genie)
  • Strong analytical background with problem-solving skills
  • Performance tuning concepts like watermarking, late data handling, parallelism & checkpointing
  • Hands-on expertise in ADF, and Qlik Replicate for data ingestion and replication
  • Experience working in Azure cloud environments
  • collaboration with cross-functional teams
  • problem-solving and analytical thinking
  • attention to data quality and governance
  • Databricks (DLT, Delta Lake)
  • Streaming technologies (Spark Structured Streaming, Autoloader)
  • Python, SQL, or Scala

Skills

What Senior Data Engineering jobs ask for — and how much of it you have →
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See also

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