Technical Lead – Data & Analytics Solutions

Job Description

Position Summary :

We are seeking a hands-on Technical Lead to drive the design, development, and delivery of robust data engineering and business intelligence solutions.

In this role, you will bridge the gap between complex data architectures and business insights, leading a team of engineers to build scalable data pipelines, secure data warehouses, and high-performance analytics dashboards.

Key Responsibilities :

– Lead and mentor a team of engineers throughout the development lifecycle, ensuring high-quality delivery.

– Design scalable, secure, and high-performing data architectures, pipelines (ETL/ELT), and analytics solutions.

– Review technical designs and code to ensure adherence to data governance and engineering best practices.

– Collaborate with Product Managers, Stakeholders, and QA/DevOps teams to align technical strategy with business goals.

– Identify technical risks, mitigate technical debt, and resolve production or performance bottlenecks.

– Estimate development efforts, support sprint planning, and continuously optimize team delivery workflows.

Required Qualifications :

– 10+ years of total software/data engineering experience, with 3+ years in a technical leadership or mentoring role.

– Strong hands-on expertise in any of the databases (Snowflake, Databricks, MSSQL) or enterprise BI tools like Tableau, Power BI.

– Deep understanding of Data Engineering concepts: ETL/ELT pipelines, Data Warehousing, and Data Quality/Governance.

– Proficiency in data-centric programming languages (preferably Python or Java).

– Solid experience working with at least one major Cloud Platform (AWS, Azure, or GCP).

– Strong analytical, problem-solving, and stakeholder management skills.

– Familiarity with Agile/Scrum methodologies.

Preferred Skills :

– Experience with Microservices or Event-Driven Architectures (Kafka/RabbitMQ).

– Familiarity with containerization (Docker) and basic CI/CD workflows.

– Exposure to Big Data technologies or Cloud Data Warehouses (Snowflake, Databricks, BigQuery).

– Knowledge of AI/ML integration concepts.

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