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Senior Data Pipeline Engineer Job Opening In India, India – Now Hiring HG Insights


Job description

At HG Insights we provides AI-powered revenue growth intelligence and technology intelligence data to help B2B companies refine their go-to-market (GTM) strategies by analyzing market size, identifying potential customers, and uncovering in-market purchasing signals.

With the recent acquisitions of MadKudu and TrustRadius, we’ve created an agentic GTM ecosystem that eliminates manual handoffs, guesswork, and siloed signals.

We’re searching for a strong Data Engineer to take this ecosystem to the next level.

You’ll play a critical role in tackling high-impact projects, including large-scale data integration, improving and enriching intent signals, and building the foundational capabilities that will power our future AI initiatives.

This is an opportunity to work with complex data pipelines at scale, shape the backbone of our intelligence platform, and directly influence how thousands of enterprise customers uncover growth opportunities.

What You Will Do

  • Build and maintain ETL pipelines using Apache Airflow in our kubernetes environment, processing 10M+ daily events from MongoDB to PostgreSQL and BigQuery
  • Design real-time data streaming architectures using Google Cloud Pub/Sub for visitor tracking, intent signals, and company resolution workflows
  • Develop ML data infrastructure for AI-powered features including vector embeddings, semantic search, and automated content generation using OpenAI and Google Vertex AI
  • Create analytics and reporting systems on BigQuery for customer intent data, lead scoring models, and business intelligence dashboards
  • Implement data quality and monitoring frameworks ensuring accuracy across the entire data pipeline from source to customer delivery
  • Build customer data delivery systems including Snowflake integration and API endpoints for enterprise data consumption

What You Will Be Responsible For

  • Data pipeline reliability with 99.9% uptime for critical business intelligence feeding customer-facing intent data products
  • Data accuracy and consistency across MongoDB → PostgreSQL → BigQuery → Snowflake transformation chains
  • ML infrastructure performance supporting real-time vector search, embedding generation, and AI model inference
  • Scalable data architecture handling exponential growth in visitor data and intent signals
  • Customer data SLAs ensuring timely delivery of intent data to enterprise customers with contractual requirements
  • Building Dashboards and alerting for management of these systems

What You Will Need

  • 9+ years data engineering with Python, SQL, and distributed data processing frameworks
  • Strong ETL/ELT experience with Apache Airflow, dbt, or similar orchestration tools
  • Cloud data platform expertise with BigQuery, Cloud Storage, and data warehouse optimization
  • Real-time streaming experience with Pub/Sub, Kafka, or similar event-driven systems
  • Database proficiency across PostgreSQL, MongoDB, and modern data warehouse technologies

Nice to Have

  • ML/AI pipeline experience with vector databases (Pinecone), embedding models, and LLM integration
  • Intent data and lead scoring domain knowledge in B2B marketing technology
  • Apache Beam or Dataflow for large-scale data processing
  • Customer analytics and behavioral data modeling experience

Required Skill Profession

Computer Occupations


  • Job Details

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Are You Looking for Senior Data Pipeline Engineer Job?

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at HG Insights adheres to the cultural norms as outlined by Expertini.

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HG Insights interview tips for Senior Data Pipeline Engineer

Here are some tips to help you prepare for and ace your Senior Data Pipeline Engineer job interview:

Before the Interview:

Research: Learn about the HG Insights's mission, values, products, and the specific job requirements and get further information about

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Be Punctual: Arrive on time to demonstrate professionalism and respect.

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Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

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Follow Up: Send a thank-you email to the interviewer within 24 hours.

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To prepare for your Senior Data Pipeline Engineer interview at HG Insights, research the company, understand the job requirements, and practice common interview questions.

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By following these tips, you can increase your chances of making a positive impression and landing the job!

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