Lead - Data Engineering at Tatvic · Ahmedabad · 6 - 9 years · ₹15L - ₹25L / yr · Bootstrapped · Posted 12 Oct 2026
1. Company Description:
Tatvic, is a marketing analytics company focusing on generating insights from data using long association with Google & its infrastructure. We breed,recognize and reward performance. As a company we are growing very fast & we are under transformation. To enable this transformation we need future leaders with eyesight which balances execution & strategic understanding.
Website: www.tatvic.com
2. Role Details
- Role: Lead Data Engineer
- Band: L4
- Department: Data Engineering
- Reporting to: L5 / Head of Delivery
- Location: Ahmedabad
- Job Type: Full Time
- Experience: 6-8 years of relevant experience
- Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related technical field.
3. Mission & Role Overview
- Mission: To create high-level organizational impact by leading a team to design and deliver scalable, high-performance cloud-native data solutions. The Lead Data Engineer (L4) is responsible for ensuring technical excellence—specifically in BigQuery optimization and secure GCP/AWS architectures—while driving the transition to Agentic AI workflows and creating value through the development of L1-L3 engineers.
- Role Overview: This is a pivotal leadership role on the Management Track, responsible for end-to-end data outcomes for the function. The Lead Engineer ensures the quality of engineering execution, manages team utilization and resource allocation, and serves as the primary technical representative in cross-functional forums with Marketing, Strategy, and Product teams.
4. Key Responsibilities
- Lead the design, development, and deployment of scalable and efficient cloud-based data pipelines and architectures.
- Build reusable data solutions and software components that serve multiple customers and use cases.
- Architect cloud environments using GCP, ensuring best practices in IAM, Security, and Networking.
- Conduct Exploratory Data Analysis (EDA) on clickstream and behavioral datasets to derive insights.
- Manage end-to-end ETL processes, including data extraction, transformation, and loading using Python, SQL, and Airflow.
- Design and build production-grade software (APIs, services, internal tools) with sound engineering practices — version control, testing, CI/CD, and code review.
- Extend data platforms with AI capabilities — integrating LLMs, RAG pipelines, and agentic workflows where they add clear business value.
- Perform Root Cause Analysis (RCA) and resolve data quality, pipeline, or application issues.
- Collaborate cross-functionally with Marketing, Insights, Product, and Engineering teams to align data initiatives with business goals.
- Document architectures, design decisions, and operations clearly and consistently.
- Coach and mentor team members, ensuring technical excellence and continuous learning.
- Participate in recruitment and knowledge-sharing through interviews, blogs, and webinars.
5. Must-Have & Good-to-Have Skills
Must-Have Skills:
- Strong understanding of clickstream data and data pipeline architecture
- Hands-on experience with cloud platforms (GCP)
- Expertise in SQL, Python, and Airflow
- Solid software engineering foundation — API design, testing, version control, and deployment practices
- Proven ability to perform exploratory data analysis and data validation
- Knowledge of cloud security, IAM, and networking best practices
- Working knowledge of building or integrating AI/LLM-based components into existing systems
- Excellent problem-solving, stakeholder management, and communication skills
Good-to-Have Skills:
- Certifications such as: Google Cloud Professional Data Engineer / Cloud Architect
- AWS Certified Data Analytics or Azure Data Engineer Associate
- Google Analytics 4 (GAIQ)
- Experience in marketing attribution, commerce data, or analytics ecosystems
- Exposure to cost optimization and cloud resource management
- Experience with agent frameworks (LangChain, ADK, MCP) or LLM APIs
- Experience building automation frameworks or internal data tools
6. Not-a-Fit Criteria
- Individual Contributor Focus: Operates as the team's best individual contributor instead of building team capability or empowering L3s.
- Information Hoarding: Keeps architectural patterns or tribal knowledge trapped in their head rather than creating reusable playbooks and documentation.
- Avoidance of Conflict: Avoids difficult performance conversations with underperforming team members, allowing capability gaps to persist.
- Activity Over Outcomes: Measures success by "tasks completed" rather than pipeline stability, data accuracy, or business impact.
- Functional Siloing: Fails to build partnerships with Marketing or Product teams, leading to misaligned data delivery.
Our Culture & Perks - Where Passion Meets Purpose:
- Competitive CTC: Based on experience and skillset
- Medical Insurance for you and your family
- Return-to-Work Program for New Moms — because career breaks shouldn’t break momentum
- 1 Work From Home Day/Month — flexibility when life calls
- 2 Birthday Leaves/Year — one for you, one for someone you love
- Monthly Engagement Activities — from game nights to learning sessions
- Inclusive Culture & Equal Opportunity Employer — diversity drives our innovation
- We Think Like Engineers & Athletes: we build, we iterate, we scale, we win — together
- 5-day workweek — because balance drives brilliance
Shubham Vishwakarma
Full Stack Developer - Averlon
About Tatvic
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Full Stack Developer - Averlon