Tech Lead

HoonarTek; Mumbai; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Hoonartek seeks a skilled data engineering specialist to advance our data platforms using Databricks, Delta Lake, and the broader lakehouse stack. You will optimize architectures, size clusters, and implement cost-aware performance tuning while building CI/CD pipelines and automation.

Exposure to AI/ML integrations, MLflow and external LLM APIs, along with cloud landing zone concepts and enterprise security, will be essential. Data modeling and warehousing know-how will guide data strategy.

Qualifications

• Hands-on knowledge of Databricks and the lakehouse stack.
• Strong understanding of Databricks architecture (control plane vs data plane).
• Experience with cluster sizing, autoscaling, cost estimation and performance tuning (FinOps).
• Experience building CI/CD pipelines and automation within Databricks.
• Exposure to AI/ML/LLM integrations (MLflow, external LLM APIs).
• Understanding of cloud landing zone concepts (subscription design, governance, policies).
• Knowledge of enterprise security architecture for data platforms.
• Data modeling incl. Dimensional and Data Vault.
• Strong data warehousing knowledge.
• Experience with API and data integration patterns.

Responsibilities

• Hands-on work with Databricks environments and pipeline orchestration.
• Optimize clusters and workloads for cost and performance.
• Develop CI/CD pipelines and automation for data engineering workflows.
• Integrate AI/ML features within the Databricks ecosystem.
• Ensure security and governance in data platforms.
• Model data using dimensional/Data Vault techniques and warehouse patterns.
• Design and implement data integration APIs and patterns.

Tools

Databricks

Delta Lake

Unity Catalog

Lakeflow

Lakebase

Databricks Apps

Workflows

ETL/ELT

CI/CD pipelines

Declarative Automation Bundle

MLflow

LLM integrations

Job description

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

• Hands on Knowledge of Databricks - Delta Lake, Unity Catalog, Lakeflow, Lakebase, Databricks Apps, Workflows, job scheduling, ETL/ ELT pipeline orchestration and more
• Strong understanding of Databricks architecture (control plane vs data plane, workspace model)
• Experience with Cluster sizing, autoscaling, and workload-based optimization, Cost estimation and performance tuning and FinOps
• Building CI/CD pipelines and Declarative Automation Bundle (DAB) implementation
• Exposure to AI/ML/LLM integrations within Databricks ecosystem (MLflow, external LLM APIs)
• Strong understanding of cloud landing zone concepts (subscription design, governance, policies)
• Understanding of enterprise security architecture for data platforms
• Data modeling: Dimensional, Data Vault
• Data warehousing
• API and data integration patterns