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into Azure Databricks. Optimize pipelines for performance, reliability, and cost, incorporating data quality checks. Develop complex transformations and processing logic using Spark (PySpark/Scala) for cleaning, enrichment, and aggregation, ensuring accuracy and consistency across the data lifecycle. Work extensively with Unity Catalog, Delta Lake, Spark SQL, and related services.

technical implications of user stories and user journeys. Coaching and mentoring team members. Minimum (essential) Requirements Strong software development experience in one of Java, Scala, or Python Software development experience with data-processing platforms from vendors such as AWS, Azure, GCP, Databricks. Experience of developing substantial components for large-scale

working with complex data pipelines, large data sets, data pipeline optimization + data architecture design. Implementing complex data transformations using Spark, PySpark or Scala + working with SQL/MySQL databases. Experience with data quality, data governance processes, Git version control + Agile development environments. Azure Data Engineer certification preferred

work scheme And More.. DATA ENGINEER - ESSTENTIAL SKILLS Proven experience building data pipelines using Databricks . Strong understanding of Apache Spark (PySpark or Scala) and Structured Streaming . Experience working with Kafka (MSK) and handling real-time data . Good knowledge of Delta Lake/Delta Live Tables

across the platform. Leverage Terraform or similar IaC tools for controlled and reproducible deployments. Databricks Development Develop and optimise data jobs using PySpark or Scala within Databricks. Implement the medallion architecture (bronze, silver, gold layers) and use Delta Lake for reliable data transactions. Manage cluster configurations and CI/

paced environment Experience in the design and deployment of production data pipelines from ingestion to consumption within a big data architecture, using Java, Python, Scala, Spark, SQL. Experience performing tasks such as writing scripts, extracting data using APIs, writing SQL queries etc. Experience in processing large amounts of structured

demonstrate the Required Skills. 3+ years of experience in data engineering, software engineering, or related fields. Strong programming skills in Python, Java, or Scala, with proficiency in data processing frameworks (e.g., Spark, Flink, or Beam). Solid understanding of data modeling, schema design, and ETL architecture. Experience working with relational

demonstrate the Required Skills. 3+ years of experience in data engineering, software engineering, or related fields. Strong programming skills in Python, Java, or Scala, with proficiency in data processing frameworks (e.g., Spark, Flink, or Beam). Solid understanding of data modeling, schema design, and ETL architecture. Experience working with relational

query optimisation). Strong experience with ETL/ELT tools. E.g. Azure Data Factory, Databricks, Synapse Pipelines, SSIS, etc. Experience with Python, PySpark, or Scala for data processing. Familiarity with CI/CD practices. Experience with Data lake, Data warehouse and Medallion architectures. Understanding of API integrations and streaming technologies

paced environment Experience in the design and deployment of production data pipelines from ingestion to consumption within a big data architecture, using Java, Python, Scala, Spark, SQL. Experience performing tasks such as writing scripts, extracting data using APIs, writing SQL queries etc. Experience in processing large amounts of structured

Proven experience as a Data Engineer, with strong background in designing and implementing data solutions in an Agile environment Proficiency in Python, Java or Scala, plus experience with SQL and NoSQL databases Experience with Microsoft SQL Server and SSRS Familiarity with cloud platforms (AWS, Azure or GCP) and containerisation (Docker

Azure technologies and identify areas for enhancement. Databricks (Unity Catalog, DLT), Data Factory, Synapse, Data Lake, Stream Analytics, Event Hubs. Strong knowledge of Python, Scala, C#, .NET. Experience with advanced SQL, T-SQL, relational databases. Azure DevOps, Terraform, BICEP, ARM templates. Distributed computing, cloud-native design patterns. Data modelling, metadata

Knowledge of DevOps practices for data pipelines Certifications: Azure Data Engineer or Azure Solutions Architect certifications Skills Mandatory Skills: Python for DATA,Java,Python,Scala,Snowflake,Azure BLOB,Azure Data Factory, Azure Functions, Azure SQL, Azure Synapse Analytics, AZURE DATA LAKE,ANSI-SQL,Databricks,HDInsight If you're excited about

Knowledge of DevOps practices for data pipelines Certifications: Azure Data Engineer or Azure Solutions Architect certifications Skills Mandatory Skills: Python for DATA,Java,Python,Scala,Snowflake,Azure BLOB,Azure Data Factory, Azure Functions, Azure SQL, Azure Synapse Analytics, AZURE DATA LAKE,ANSI-SQL,Databricks,HDInsight If you're excited about

Azure cloud experience Experience with data modelling, data integration ETL processes and designing efficient data structures Strong programming skills in Python, Java, or Scala Data warehousing concepts and dimensional modelling experience Any data engineering skills in Azure Databricks and Microsoft Fabric would be a bonus This new role involves leading

Experience: Proven experience as a Data Engineer or similar role, with strong knowledge of data warehousing and modelling. Proficiency in C#, Python, Java, or Scala . Hands-on experience with ETL tools (e.g., SSIS) and orchestration tools (e.g., Azure Data Factory). Strong SQL skills and experience with relational databases

have the following characteristics, it would be a plus: Deep knowledge and use of at least one common programming language: e.g., Python, Scala, Java, including toolchains for documentation, testing, and operations/observability Deep expertise in modern software development tools/ways of working (e.g. git/GitHub, DevOps tools

ingest, transform, and load data from diverse sources (APIs, databases, files) into Azure Databricks. Implement data cleaning, validation, and enrichment using Spark (PySpark/Scala) and related tools to ensure quality and consistency. Utilize Unity Catalog, Delta Lake, Spark SQL, and best practices for Databricks development, optimization, and deployment. Program

services, data processing, and cloud tooling. Proficiency in building, testing, and optimizing production-grade data pipelines using tools such as Databricks, Spark (PySpark/Scala), and SQL. Experience implementing and managing continuous integration and delivery (CI/CD) pipelines (e.g., GitLab CI) and using Docker for containerization. Experience designing, deploying

problems in a business environment setting. Relevant Experience Experience with machine learning technology, such as: big data, Java, Python, R, AWS, LLM models,. Scala and visualization techniques, including Dash, Tableau and Angular. Experience in understanding brand content, strategy, and tactics. Ability to effectively utilize dashboards and data products

frameworks and technologies Experience with data modelling, Databricks, data integration ETL processes and designing efficient data structures Strong programming skills in Python, Java, or Scala Data warehousing concepts and dimensional modelling experience Any data engineering skills in Azure Databricks and Microsoft Fabric would be a bonus This new role involves

frameworks and technologies Experience with data modelling, Databricks, data integration ETL processes and designing efficient data structures Strong programming skills in Python, Java, or Scala Data warehousing concepts and dimensional modelling experience Any data engineering skills in Azure Databricks and Microsoft Fabric would be a bonus This new role involves

significant focus on data engineering or analytics. Proficiency in building, testing, and optimizing production-grade data pipelines in Databricks, using Spark (PySpark/Scala) and SQL. Strong Python and SQL skills. Hands-on experience developing dashboards for analysis and reporting, leveraging tools such as Databricks Workspaces, Streamlit or Jupyter notebooks.

/WFS services, graph theory (NetworkX), GDAL, and Snowflake. Nice to have: CI/CD and orchestration tools (Airflow, Argo CD), Mapbox/MapLibre, Scala, Streamlit, DuckDB, and Power BI. What you need to do now If you're interested in this role, click 'apply now' to forward

data warehousing concepts Experience of deploying data-processing platforms from vendors such as AWS, Azure, GCP, Databricks. Comfortable in one or more of Java, Scala, or Python with the ability to be ‘hands on’ when required We are passionate about developing people – a demonstrated ability in managing, coaching and developing