Lead Analytics Engineer

Job highlights

• Academics UG: BE / BTech,PG: Post Graduation is not compulsory. Job Profile and Responsibilities
• Skills Required: .
• Experience: 5 - 10 years of relevant experience in the Analytics industry. Job .
• Desired Candidate Profile: . 5+ years of experience in Data Engineering,with at least 2-3 years in a technical leadership or architecture role.

Lead Analytics Engineer

Experience: 5 - 10 years of relevant experience in the Analytics industry

Job

Academics UG: B.E / B.Tech, PG: Post Graduation is not compulsory

Job Profile and Responsibilities

About This Role:

As a Lead Analytics Engineer, you will be responsible for architecting, designing, and implementing advanced data platforms, AI/ML pipelines, and analytics solutions that drive critical business insights for clients across global geographies and industry verticals. You will act as the technical authority for multiple data engineering and AI projects, guiding teams in best practices for data architecture, DataOps, and governance. This role demands a combination of hands-on expertise, strategic client advisory, and the ability to translate complex business objectives into scalable, high-performance data solutions.
You will collaborate closely with clients, data engineers, data scientists and internal leadership to ensure delivery of robust, secure, and high-performance data platforms that empower analytics and decision-making.

Key Responsibilities:

• Client Advisory Stakeholder Management: Interface with clients across global geographies and business verticals (Ecommerce, Telecom, BFSI, Pharmaceuticals, Manufacturing, Media, Sports, etc.) to understand business objectives, translate requirements, and deliver actionable, implementable solutions.
• Solution Data Architecture: Design and own scalable, secure, and high-performance data architectures across cloud (AWS, GCP, Azure, OCI), multi-cloud, and hybrid environments.
• Data Engineering ETL Pipelines: Architect and manage robust ETL/ELT pipelines, orchestration frameworks, and modern data warehousing solutions across cloud platforms, Databricks, Snowflake, and Apache environments.
• Advanced AI GenAI Solutions: Drive large-scale AI solution architecture, including GenAI/LLM-driven AI Agents, Retrieval-Augmented Generation (RAG) workflows, Vector DBs, and specialized AI/ML models (Computer Vision, Speech Engineering, Spatial Modeling).
• DataOps DevOps Implementation: Define and implement DataOps, DevOps, and CI/CD frameworks to ensure automation, testing, monitoring, and high availability of data workflows.
• Full-Stack Visualization Oversight: Oversee full-stack data application development (Python, PySpark, Node.js, React.js) and Business Intelligence dashboard creation (Tableau, Power BI, Looker, Domo, Qlik Sense, Metabase).
• Leadership Team Mentorship: Mentor and guide a team of data engineers and analysts; perform code reviews, enforce engineering best practices, and cultivate technical excellence.
• End-to-End Ownership: Take complete ownership of projects, manage technical documentation and delivery timelines, and delight clients at every touchpoint through impeccable solution delivery and clear communication.

Skills Required:

• Programming Full-Stack Development: Python, PySpark, SQL, Node.js, React.js
• ETL, Orchestration Pipelines: Airflow, dbt, Fivetran, Talend, Glue, Apache ecosystem tools
• Databases, Warehouses Storage: BigQuery, Redshift, Snowflake, Databricks, Data Lake, RDS, MongoDB, Cassandra, Neo4j, Vector DBs
• Cloud Platforms: AWS, GCP, MS Azure, OCI, Databricks, Snowflake
• AI, Machine Learning GenAI: LLMs, RAG, AI Agents, Vector DBs, Computer Vision, Speech Engineering, Spatial Modeling
• Business Intelligence Visualization: Tableau, Microsoft Power BI, Qlik Sense, Domo, Looker, Metabase
• CI/CD DevOps: Git, Jenkins, GitLab CI, Docker, Kubernetes, Terraform, CloudFormation
• Monitoring Logging: Prometheus, Grafana, ELK
• APIs Integration: REST/SOAP APIs, Microservices architecture

Desired Candidate Profile:

• 5+ years of experience in Data Engineering, with at least 2-3 years in a technical leadership or architecture role.
• Proven ability to lead teams, manage clients, and deliver complex data solutions.
• Strong analytical, problem-solving, and communication skills.
• Eye for detail and passion for building efficient, reliable, and maintainable data systems.
• Ability to thrive in a fast-paced, client-focused environment.
• Cloud or Data Engineering certifications (AWS, GCP, Azure, Snowflake, Databricks).

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.