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Senior Data Engineer-Databricks
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Kharadi
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About Us
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We empower enterprises globally through intelligent, creative, and insightful services for data integration, data analytics and data visualization.
Hoonartek is a leader in enterprise transformation, data engineering and an acknowledged world-class Ab Initio delivery partner.
Using centuries of cumulative experience, research and leadership, we help our clients eliminate the complexities & risk of legacy modernization and safely deliver big data hubs, operational data integration, business intelligence, risk & compliance solutions and traditional data warehouses & marts.
At Hoonartek, we work to ensure that our customers, partners and employees all benefit from our unstinting commitment to delivery, quality and value. Hoonartek is increasingly the choice for customers seeking a trusted partner of vision, value and integrity
How We Work?
Define, Design and Deliver (D3) is our in-house delivery philosophy. It’s culled from agile and rapid methodologies and focused on ‘just enough design’. We embrace this philosophy in everything we do, leading to numerous client success stories and indeed to our own success.
We embrace change, empowering and trusting our people and building long and valuable relationships with our employees, our customers and our partners. We work flexibly, even adopting traditional/waterfall methods where circumstances demand it. At Hoonartek, the focus is always on delivery and value.
Job Description
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We are seeking an experienced Senior Data Engineer – Databricks to design, develop, and optimize scalable data platforms using the Databricks Lakehouse architecture. The ideal candidate will have deep expertise in building modern data pipelines, implementing Delta Lake best practices, and leveraging the latest Databricks capabilities including Auto Loader, Spark Declarative Pipelines (SDP/DLT), Databricks Workflows, Unity Catalog, and AI/BI features.
The role requires strong hands-on development skills, the ability to mentor team members, and experience delivering enterprise-grade data engineering solutions on cloud platforms.
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Job Requirement
Strong proficiency in PySpark and SQL for large-scale data processing.
Practical experience with Delta Lake / Delta Tables (ACID transactions, schema enforcement, versioning).
Experience building ingestion pipelines with Auto Loader (cloudFiles, schema inference/evolution).
Hands-on experience with SDP (Spark Declarative Pipelines / DLT) for building declarative data pipelines.
Experience orchestrating pipelines with Databricks Workflows (jobs, tasks, triggers).
Solid understanding of Unity Catalog for governance, permissions, and metastore management.
Good grasp of data warehouse concepts — dimensional modeling, data marts, slowly changing dimensions.
Experience building or supporting AI/BI dashboards (Databricks SQL Dashboards, Genie, or similar BI tools).
Familiarity with cloud platforms (Azure/AWS/GCP) and cloud storage integration
