--- title: 'Associate Customer Experience Engineer at Hevo Data' canonical: 'https://feeny.ai/job/associate-customer-experience-engineer-hevo-data-pune-yxt5xjwzxcnc' type: 'job' last_seen: '2026-10-12' --- # Associate Customer Experience Engineer at Hevo Data - **Company:** Hevo Data - **Location:** Pune, India - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-09-25 - **Last confirmed live:** 2026-10-12 - **Apply:** https://jobs.lever.co/hevodata/96993ebc-609a-4733-84cd-e1a0c3e69fda ## Job description ## About Hevo Hevo Data is a no-code data pipeline platform that helps companies consolidate data from multiple sources for faster analytics. Our fully managed pipelines let data teams move data from 150+ sources (databases, SaaS applications, cloud storage, SDKs, streaming services) into warehouses and lakes, all without writing code. Over 2,000 data teams in 45+ countries use Hevo, including DoorDash, Foot Locker, Arhaus, and Santander. We’re top-rated in the G2 Data Pipeline category, backed by Sequoia Capital, Qualgro, and Chiratae Ventures, and operate out of San Francisco and Bangalore. ## Role Summary An Associate Customer Experience Engineer owns customer issues end-to-end, keeps unnecessary escalations to a minimum, and ensures every interaction reflects a high standard of customer experience. This role centers on troubleshooting JDBC-based sources and integrations, partnering closely with Product and Engineering whenever an issue calls for deeper investigation. The role calls for building solid technical depth over time, following and refining support workflows, putting AI and automation to good use, and adding to the team's shared knowledge so issues get resolved faster and more consistently across the board. ## Key Responsibilities Own customer issues and drive them to resolution within SLA timelines, combining structured investigation with clear, timely updates to the customer. Investigate issues by digging into SQL, logs, API responses, database behavior, product documentation, and other diagnostic tools available. Loop in Product and Engineering as needed, sharing the relevant technical context, investigation findings, and steps to reproduce the issue. Keep unnecessary escalations to a minimum by building strong product and technical knowledge and resolving issues independently wherever possible. Follow established support processes and flag improvements that cut down on rework, manual effort, and resolution time. Use AI-assisted tools, automation, and diagnostic capabilities to make troubleshooting faster and more consistent. Build deeper technical expertise in JDBC-based sources and integrations, along with databases, APIs, ETL, and related technologies. Add to SOPs, KB articles, onboarding material, and other knowledge assets the wider team relies on. Support teammates when needed and take an active part in team training, enablement, and knowledge-sharing activities. What Success Looks Like Steady SLA adherence combined with consistently high-quality resolutions on owned tickets. A growing ability to resolve technically complex issues without outside help. An avoidable escalation rate that stays low and keeps trending downward. Customer communication that is clear, accurate, and easy to act on. Meaningful, ongoing contributions to SOPs, KBs, and broader team enablement. Real, measurable use of AI and automation to cut down on manual effort and resolution time. Visible growth in technical depth and troubleshooting capability over time. Required Skills & Experience Solid grasp of cloud technologies and core database concepts, including the basics of database administration. Hands-on experience troubleshooting databases, applications, or integrations. Strong command of SQL. Familiarity with data warehousing, ETL, REST APIs, and webhooks. Working knowledge of Java or another object-oriented programming language. Sharp troubleshooting, debugging, research, and problem-solving abilities. Background in technical product support, including email-based support. Able to write and maintain clear technical documentation such as KBs and SOPs. Strong written and verbal communication with a sharp eye for detail. Genuinely curious and customer-first, with the ability to break down and synthesize technical information effectively. ## Preferred Qualifications 1–3 years in technical product support, application support, database support, or a similar technical role. Hands-on experience troubleshooting JDBC-based sources or integrations. DBA experience with PostgreSQL, MySQL, SQL Server, Oracle, or a similar database platform. Background supporting B2B SaaS products or integration platforms. Exposure to ETL/data integration platforms. ## About Hevo Data ## Company Overview - **One-liner**: Hevo Data provides an automated, no-code data pipeline platform that enables companies to ingest, transform, and load data from 150+ sources into any data warehouse or destination. - **Entity Type**: Private (Series B, raised $43M total) - **Headquarters**: San Francisco, California, United States (with major offices in Bengaluru and Pune, India) - **Founded**: 2017 - **Founders**: Manish Jethani (Co-Founder & CEO) ## Core Business - **Primary industry**: Data Infrastructure / ETL (Extract, Transform, Load) / Data Integration - **Target customers**: B2B – mid-market and enterprise companies that need to unify data from multiple SaaS, database, and file storage sources for analytics. - **Mission or purpose statement**: “Build Data Platform for Data-Driven People” – helping companies access, model, and consume petabytes of data in real-time. ## Products & Services - **[Hevo Data Platform](https://hevodata.com)**: A fully managed, no-code data pipeline service that supports 150+ pre-built connectors, real-time CDC (Change Data Capture), schema drift handling, and dbt-based transformations. Available as a SaaS platform. ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed - **Key Metric**: Annual Revenue – **$46.9M** (2024, per Latka); conflicting estimate of $5M (LinkedIn, likely outdated). **Total Funding**: $43M across 4 rounds (Seed in 2017, Seed in 2019, Series A in 2020, Series B in 2021). - **Notable Investors/Partners**: Sequoia Capital India (led $30M Series B), with additional investors from earlier rounds. Recognized as a partner by Snowflake and Google Cloud. - **Growth Signals**: - Processes **1PB+ data monthly**; trusted by **2,000+ companies** worldwide. - Headcount: ~182 (LinkedIn, 2026) vs ~242 (Latka, 2026) – conflicting reports, but indicates a lean team. - Expanding into new geographies (San Francisco, Bengaluru, Pune, Singapore, Germany) and building new products. - Revenue grew from $31.2M (2023) to $46.9M (2024) per Latka. ## Competitive Advantages - **Zero-code, zero-maintenance**: Set up pipelines in minutes without engineering overhead; automatically handles schema drifts, API changes, and record failures. - **Scalability**: Handles massive data volumes (10x+ growth) without infrastructure changes, with high-throughput CDC replication. - **150+ pre-built connectors** and custom connector development service. - **End-to-end ELT** – combines extraction, loading, and dbt-based modeling in one platform with full pipeline observability. ## Strategic Focus - Continue building “Data Infrastructure as a Service” for hundreds of thousands of companies. - Invest in new product lines, geographic expansion, and open-source contributions. - CEO describes the company as “only 2% done,” emphasizing a long‑term growth trajectory. ## Why Work Here - **Culture**: Data‑driven, engineering‑heavy, with a “day one” mentality. Strong commitment to open‑source (engineers encouraged to open‑source components). - **Work policy**: Hybrid/office‑based – roles in San Francisco, Bengaluru, and Pune are listed as on‑site; some “Worldwide” remote options may exist but are not common. - **Notable perks**: Competitive salaries (e.g., Senior Software Engineer ~INR 4.1M/year), strong employer rating (4.1/5 on LinkedIn) with high marks for compensation (4.2) and career growth (4.1). - **Engineering culture**: Focus on low‑level data infrastructure, real‑time pipelines, and building scalable systems. Alumni have moved to top tech companies (Google, Confluent, Adobe, Fivetran). ## Sources 1. [hevodata.com](https://hevodata.com) 2. [jobs.lever.co/hevodata](https://jobs.lever.co/hevodata) 3. [linkedin.com/company/hevodata](https://www.linkedin.com/company/hevodata) 4. 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