Miratech
Information Technology And Services
DataEngineer(AzureDatabricks)
Neural analysis suggests this role is
optimal for mid candidates.
“Data Engineer (Azure Databricks) at Miratech. Skills: Azure Databricks, Data pipelines, Lakehouse architectures, PySpark, Spark SQL, Delta Lake, Azure Data Factory. Design, develop, and maintain data pipelines using Azure Databricks. Build and optimize data transformations using PySpark and SQL in Databricks”
What You'll Achieve.
Enable advanced analytics and business intelligence; Meet or exceed scope, schedule, and/or budget objectives
Industry & Context.
What They're Looking For.
Must Have
3+ years of experience in Data Engineering or Data Warehouse development, experience with Azure Databricks, Experience developing data pipelines using PySpark and Spark SQL, Solid understanding of distributed data processing and big data concepts, Experience working with Delta Lake and Lakehouse architectures, SQL skills and experience with SQL Server relational databases, Experience building data pipelines using Azure Data Factory, Experience handling large datasets and performance optimization
Nice to Have
Experience with Spark optimization techniques (partitioning, caching, cluster tuning), Experience with structured streaming in Databricks, Knowledge of CI/CD pipelines for data platforms (Azure Devops), Familiarity with Power BI, Experience in migrating from traditional ETL process to cloud architectures
What You'll Do.
and maintain data pipelines using Azure Databricks
Build and optimize data transformations using PySpark and SQL in Databricks
Implement and maintain Lakehouse architectures using Delta Lake
Develop ETL/ELT pipelines orchestrated through Azure Data Factory
Integrate data from multiple sources into the data platform and analytical layers
Design and maintain data models and data warehouse structures for analytics
and performance of large-scale data processing pipelines
Collaborate with BI teams to support Power BI and reporting platforms
Support and evolve existing SQL Server data platforms and ETL solutions (SSIS) when required
Contribute to the design of modern cloud-based data architectures
How You'll Work.
Team & Collaboration
Collaborate with BI teams to support Power BI and reporting platforms
Communication Scope
Open communication
Full Job Description
Miratech helps visionaries change the world. We are a global IT services and consulting company that brings together enterprise and start-up innovation. Today, we support digital transformation for some of the world's largest enterprises. By partnering with both large and small players, we stay at the leading edge of technology, remain nimble even as a global leader, and create technology that helps our clients further enhance their business. We are a values-driven organization and our culture of Relentless Performance has enabled over 99% of Miratech's engagements to succeed by meeting or exceeding our scope, schedule, and/or budget objectives since our inception in 1989. Miratech has coverage across 5 continents and operates in over 25 countries around the world. Miratech retains nearly 1000 full-time professionals, and our annual growth rate exceeds 25%. We are looking for a Middle Data Engineer specialized in Azure Databricks to join our data platform team. The candidate will design and develop modern data pipelines and Lakehouse architectures, leveraging Azure Databricks, Spark, and Azure Data Factory, while integrating with existing SQL Server-based data warehouse environments, also evolving our data platform towards scalable, cloud-based data architectures, enabling advanced analytics and business intelligence. Key responsibilities: * Design, develop, and maintain data pipelines using Azure Databricks * Build and optimize data transformations using PySpark and SQL in Databricks * Implement and maintain Lakehouse architectures using Delta Lake * Develop ETL/ELT pipelines orchestrated through Azure Data Factory * Integrate data from multiple sources into the data platform and analytical layers * Design and maintain data models and data warehouse structures for analytics * Ensure data quality, scalability, and performance of large-scale data processing pipelines * Collaborate with BI teams to support Power BI and reporting platforms * Support and evolve existing
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