Data Engineer

1. Company Description

Tatvic Digital Analytics is a Google Premier Partner specializing in Marketing Analytics, Cloud, and AI solutions. With 16+ years of experience, Tatvic works with leading enterprises across BFSI, Auto, OTT, and Retail to unlock growth using data and intelligence. As part of our next phase, we are building cutting-edge capabilities in Cloud, Agentic AI, and automations to transform decision-making systems and deriving insights.

Website: https://www.tatvic.com/

2. Role Overview & Metadata

• Role: L2 Data Engineer
• Band Details: L2 (Senior Specialist)
• Department: Data Engineering
• Reporting To: Data Engineer Lead
• Location: Ahmedabad (Work from Office)
• Job Type: Full Time
• Work Mode: Onsite
• Experience: 2-4 years of relevant experience in building ETL pipelines and cloud data solution.
• Education: Bachelor’s or Master’s degree in Computer Science, Computer Engineering or a related technical field.

3. Key Responsibilities

• Provision, configure, and manage GCP resource-
• Implement and maintain cloud governance practices - IAM role management, project structuring, access contro and Networking best practices.
• Monitor cloud costs, usage, and billing; assist with optimization recommendations.
• Provide reliable technical input for proposals, including accurate effort estimates and feasibility assessments.
• Research and introduce innovative technologies and methodologies into the existing cloud infrastructure to improve architecture.
• Design and build reusable, scalable cloud solutions and ETL pipelines that can be deployed across multiple customers.
• Collaborate with analytics/BI teams to understand data requirements and translate them into pipeline solutions or
• Write efficient, optimized SQL queries and manage BigQuery datasets, partitioning, and clustering strategies.
• Build and maintain data models to support BI/reporting needs.
• Ensure data quality, consistency, and reliability across pipelines.
• Perform Root Cause Analysis (RCA) and resolve complex data issues specifically for Marketing Attribution and user behavioral datasets.
• Monitor data pipelines, troubleshoot technical failures, and resolve them proactively to ensure data continuity.
• Perform rigorous User Acceptance Testing (UAT) on datasets following the ETL process to ensure business alignment and KPIs.
• Work closely with clients/stakeholders to understand technical requirements and translate them into scalable solutions.
• Participate in code reviews and follow engineering best practices (version control, CI/CD basics)
• Mentor juniors to improve team effectiveness; specifically identify team members ready for a band change and provide the required guidance to prepare them for advancement.
• Create comprehensive documentation regarding architecture, design concepts, and data operations for long-term institutional knowledge. While also writing and maintaining runbooks/SOPs for common cloud operations tasks.

4. Must-Have Skills

• SQL Proficiency: Advanced knowledge of Analytical, Window, and Navigation functions, query optimizations, CTEs .
• Python: Expert application of Python and DataFrames for complex data processing and automation.
• ETL Pipeline: Experience building data pipelines (batch/streaming) using tools like Dataflow, Cloud Composer, or similar from raw clickstream data or equivalent data sources.
• Cloud Platforms (GCP): Hands-on experience with Compute, Networking, and Security services.(eg. BigQuery, Cloud Storage, IAM, Compute Engine, Cloud Run).
• Understanding of IAM and cloud security fundamentals
• Experience with version control (Git) and CI/CD.
• Knowledge of cost optimization strategies (CUDs, budget alerts, billing exports).
• Statistics: Foundational understanding of statistical aggregations and functions (e.g., quantiles) for data analysis.
• Airflow: Experience in scheduling and managing complex, interdependent data workflows.
• Exploratory Data Analysis: Demonstrated ability to find anomalies and derive actionable stories from raw data.

5. Good-to-Have Skills

• Understanding of data governance frameworks.
• Exposure to Looker/LookML or other BI tools
• Familiarity with Terraform or other IaC tools for GCP provisioning
• Databricks: Experience with unified data analytics and processing platforms.
• Google Cloud Professional Data Engineer Certification: Verified expertise in designing and building data processing systems.
• Google Analytics 4 Certification (GAIQ): Proficiency in the GA4 data model and behavioral measurement.

6. Not-a-Fit Criteria

• Operating at L1 Level: Work consistently requires constant pre-review or heavy supervision before it is ready for client delivery, creating a bottleneck for senior team members.
• Reactive Problem Solving: Escalates technical blockers to management without performing initial analysis or proposing potential solutions.
• Communication Gaps: Fails to communicate project risks or delivery delays until the deadline has already passed.
• Relationship Avoidance: Avoids direct communication with clients or hides client dissatisfaction from the reporting manager, hindering proactive intervention.

7.Our Culture & Perks

• Competitive CTC: based on experience & skillset
• Medical Insurance for you & your family
• Return-to-Work Program for new moms
• 2 Birthday Leaves/Year - for you & someone special
• 1 WFH Day/Month
• Monthly Engagement Activities - sports, games, team-offs
• Inclusive, Diverse Culture - your uniqueness is your superpower
• Growth-first Environment - where learning never stops
• 5-Day Workweek - we protect your weekends.