Design and architect large-scale Azure data lakehouse infrastructure and ETL/ELT pipelines. Optimize Databricks and Data Lake costs, troubleshoot production failures, improve data quality and reliability, and implement governance and security best practices. Collaborate with and mentor global data scientists, analysts, and operations teams while delivering secure, automated solutions using Azure, Spark, Python, and Scala.
About Tarento:
Tarento is a fast-growing technology consulting company headquartered in Stockholm, with a strong presence in India and clients across the globe. We specialize in digital transformation, product engineering, and enterprise solutions, working across diverse industries including retail, manufacturing, and healthcare. Our teams combine Nordic values with Indian expertise to deliver innovative, scalable, and high-impact solutions.
Senior Data Engineer (Azure Databricks)
Lead design and architecture of large-scale data infrastructure and pipelines (Data Lakehouse).
Transform complex business requirements into automated, secure data solutions (ETL/ELT) primarily in Azure.
Optimize data storage and compute costs across Databricks clusters and Data Lake.
Troubleshoot and resolve production pipeline failures and data quality issues.
Drive best practices in data governance, security, and pipeline reliability.
Mentor and coordinate with global teams (data scientists, analysts, operations).
Required Skills & Experience:
5–8 years (often 8+ in practice) in data engineering or platform roles.
Expert hands-on experience with Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
Deep SQL and data modelling skills (OLAP, OLTP, dimensional modelling).
Proficiency in Python/Scala for Spark jobs and data transformation.
Understanding of Azure Data Lake Storage optimizations and Azure resource cost tuning.
Experience implementing CI/CD and IaC for data pipelines.
Knowledge of data security/compliance (RBAC, encryption, GDPR principles).
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