Merkle
DataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Data Engineer at Merkle. Skills: Azure, Databricks, Data Engineering, SQL, Python. Build scalable ETL/ELT pipelines. Develop SQL-based transformations”
Industry & Context.
Troubleshoot pipeline failures; Root-cause analysis
What They're Looking For.
Must Have
3+ years of experience, Hands-on Azure data services, SQL skills, Python skills
Nice to Have
Exposure to streaming technologies, Familiarity with Lakehouse architecture, Familiarity with Delta Lake concepts, Experience integrating Azure data platforms with BI tools, Basic knowledge of data governance, Basic knowledge of data quality frameworks, Awareness of Azure cost-optimization best practices, Experience working in Agile delivery models
What You'll Do.
Build scalable ETL/ELT pipelines
Develop SQL-based transformations
Develop Python/PySpark pipelines
Ingest data using ADF
Process data using ADF
Ingest data using Databricks
Process data using Databricks
Ingest data using ADLS
Process data using ADLS
Build analytics-ready data models
Support deployment of data pipelines
Support execution of data pipelines
Monitor data pipeline health
Monitor data pipeline performance
Perform root-cause analysis
Follow Azure security best practices
Follow Azure reliability best practices
Follow Azure scalability best practices
Work with product teams
Translate business needs
Translate analytics needs
Contribute to documentation
Contribute to code reviews
Contribute to engineering standards
How You'll Work.
Team & Collaboration
Collaborate with architects; Collaborate with analytics teams; Collaborate with QA; Collaborate with DevOps; Collaborate with business stakeholders; Collaborate with product teams
Communication Scope
Explaining technical concepts
Process & Methodology
Agile delivery models
Full Job Description
**Job Description:** Job Description Details **Business Title** Data Engineer **Years of Experience** Min 3 and max upto 7. **Job Descreption** Looking for a hands‑on Senior Data Engineer – Azure & Databricks with up to 6 years of total experience to build, optimize, and maintain scalable cloud data platforms. This is an individual contributor role, focused on developing reliable data pipelines and analytics‑ready datasets using Microsoft Azure and Databricks. The role requires strong hands‑on expertise in SQL and Python, along with experience building batch (and basic streaming) data pipelines in a cloud environment. You will collaborate closely with architects, analytics teams, QA, DevOps, and business stakeholders in a global delivery model. Must have skillsHands‑on experience delivering Azure‑based data engineering solutions Cloud & Data Engineering (Azure) Strong hands‑on experience with Azure data services, including: Azure Data Lake Storage Gen2 (ADLS) Azure Data Factory (ADF) Azure Databricks Azure Synapse Analytics Experience designing cloud‑native data lakes and analytical data stores Solid understanding of batch data pipelines and basic streaming concepts SQL & Python (Mandatory) Strong SQL skills (mandatory) Writing complex queries, joins, aggregations, and transformations Hands‑on experience working with large datasets in Synapse / Databricks Strong Python skills (mandatory) Python for ETL / ELT and data engineering use cases Hands‑on experience with PySpark in Databricks Strong understanding of data modeling, transformations, and query performance tuning Data Processing & Engineering Hands‑on experience with Spark / PySpark on Databricks Experience handling structured and semi‑structured data Understanding of partitioning, schema evolution, and data validation concepts DevOps & Platform Basics Working knowledge of Infrastructure as Code (ARM Templates and/or Terraform) Basic experience with CI/CD pipelines (Azure DevOps or GitHub Actions) Understanding
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