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Data Integration Full-time
Lead Data Engineer
India Office
Reports to: Senior Director – Forward Deployment
About Terrantic
Terrantic builds AI-powered operations software for fresh food processors—packhouses, growers, co-ops, and food manufacturers. We help operations teams who've been running on spreadsheets and gut instinct finally get real visibility into what's happening on their floor, in their storage, and across their supply chain.
Our platform connects to the messy reality of food processing: ERPs that were installed 15 years ago, PLCs on aging pack-lines, WMS systems that don't talk to anything else. We pull it all together, make sense of it, and use AI agents to automate decisions that used to require someone walking the floor at 5 AM.
The Role
We are looking for a Lead Data Engineer to own our Data Integration track. You will not only design robust integration architectures but also lead the successful implementation of these systems by guiding a team of 2–3 engineers. This is a "Player-Coach" role: you are expected to remain hands-on with code and architecture while ensuring the team delivers high-quality data pipelines faster that meet strict SLAs.
Today, you'll lead a team of about 2 engineers. Over the next 12-14 months, you'll grow that to 5+ team.
This is a player-coach role. You will guide the team in design, develop and deploy the pipelines and integrations and it's an extremely hands-on role which requires you to also develop/validate/deploy components as we grow.
What You'll Do
Technical Leadership & Implementation
- Lead the Squad: Manage, mentor, and conduct code reviews for a team of 2–3 Data Engineers. Drive sprint planning, estimation, and task delegation to ensure successful delivery
- Integration Architecture: Design scalable, fault-tolerant ETL/ELT frameworks to ingest complex data from diverse sources (REST APIs, Streaming logs, CRM/ERP systems) into our central repository
- Implementation Ownership: Take full accountability for the "Implementation" phase of the software lifecycle. Ensure that architectural designs are translated into functioning, production-grade code by the team
Engineering & Optimization
- Advanced Pipeline Development: Handle the most complex transformations and architectural challenges. Move beyond simple ingestion to building self-healing and idempotent pipelines
- Performance Tuning: Write and optimize complex SQL queries and Python scripts. Identify bottlenecks in the Data Warehouse/Lake and implement indexing, partitioning, or schema changes to improve performance
- Code Quality Standards: Enforce version control best practices, CI/CD workflows, and run data validations within the team
- AI/ML: Collaborate directly with Data Scientists and ML Engineers to understand their feature requirements and build high-quality, production-ready pipelines. Engineer and manage the data infrastructure required for model training datasets, including versioning, lineage tracking, and compliance
Reliability & Stakeholder Management
- SLA Management & RCA: Lead the resolution of critical incidents (P0/P1). Move beyond "debugging" to performing Root Cause Analysis (RCA) to prevent recurrence and ensure customer SLAs are met
- Data Quality Governance: Define the strategy for monitoring and alerting. Ensure the team implements automated checks for data accuracy, freshness, and completeness
- Collaboration: Act as the technical point of contact for Product Managers and Architects. Translate high-level business requirements into technical tickets for your team
What We're Looking For
Required
- 5+ years of professional experience in Data Engineering
- Minimum 2 years of experience leading, mentoring, or managing a small team (formal or informal)
- Must be willing to work extended hours (to overlap US Time Zone). You will be the primary technical lead during these hours, ensuring unblocked development and rapid incident response
- Still an active coder—you've shipped production grade pipelines and orchestrated the flow in the last 6 months, not just managed people who did
- Strong communication skills—you can explain complex technical decisions to non-technical stakeholders clearly
Technical Competencies
- Database Mastery: Expert-level proficiency in SQL (PostgreSQL, ClickHouse, MySQL) and good experience with Data Warehousing modeling (Star/Snowflake schemas, SCDs)
- Code Proficiency: Good programming skills in Python (Pandas, PySpark, async libraries)
- Orchestration & Integration: Hands-on experience with modern data stack tools is mandatory (e.g., Airflow, NiFi etc)
- Cloud Native: Proven experience implementing pipelines on Hyperscalers (AWS, Azure, or GCP) using services like S3, Lambda/Functions, EMR, or Redshift/Synapse
Soft Skills
- Delivery Focused: A mindset geared towards "getting things done in the right and optimal manner". Your focus would be on shipping working code and enabling the team to deliver without compromising on quality of deliverables
- Communication: Ability to explain complex technical issues to non-technical stakeholders during US business hours
Nice to Have
- Experience with Infrastructure as Code (Terraform, CloudFormation)
- Experience implementing Data Quality tools
- Knowledge of Containerization (Docker, Kubernetes) for deploying data apps
What We Offer
- Competitive salary (commensurate with experience and startup stage)
- Meaningful equity in a growing company
- Flexible remote work with occasional travel
- A team that respects your time and trusts you to lead
- Real problems worth solving—food waste is a $400B problem and we're actually fixing it
How to Apply
Send a note to hr@terrantic.com with:
- 1 Your resume
- 2 A few sentences on why this role interests you
- 3 An example of a technical or organizational challenge you navigated while scaling a team
Terrantic is an equal opportunity employer. We value diverse perspectives and believe the best teams are built by people with different backgrounds and experiences.