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Konovo

Connects healthcare audiences with real-time insights

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • At least 5 years of experience building and operating production data pipelines, specifically in data engineering rather than primarily business intelligence, analytics, or data science.
  • Strong SQL and data modeling skills, including dimensional and/or lakehouse modeling.
  • Hands-on production experience with Databricks and Spark, including debugging, performance tuning, and cost awareness.
  • Experience building batch extract-load-transform pipelines at frequent cadence, including idempotency, backfills, and late-arriving data patterns.
  • Experience with orchestration and transformation tools such as Airflow and dbt, along with version control and continuous integration/continuous delivery practices.
  • Strong data quality discipline, including automated tests or expectations, monitoring and alerting, and clear service-level agreements for critical datasets.
  • Ability to own production systems, including triage, incident response, and continuous improvement.
  • Clear written and verbal communication for engineering work, including requirements clarification, design documentation, and tradeoff analysis.
  • Willingness and ability to work in a hybrid arrangement in Bengaluru (Whitefield) and overlap 3–4 hours with Eastern Standard Time.

Responsibilities

  • Build and own production-grade batch extract-load-transform pipelines in Databricks and Spark on 15-minute working-hours and hourly off-hours cadences.
  • Design, scale, and operate the lakehouse using Bronze, Silver, and Gold medallion patterns, including incremental loads, backfills, and late-arriving data handling.
  • Create curated and well-documented data products that are reusable across teams and trusted for decision-making.
  • Improve reliability through automated testing, monitoring and alerting, and clear service-level agreements for critical pipelines and tables.
  • Partner with engineering and business stakeholders to translate needs into durable data models rather than one-off extracts.
  • Implement data governance and security expectations through access controls, lineage, and quality standards.

Desired Qualifications

  • Deep Delta Lake experience, including schema evolution, OPTIMIZE/Z-ORDER, compaction, and partitioning strategy.
  • Experience with change data capture ingestion patterns such as Debezium, Fivetran, HVR, or custom change data capture, including late or out-of-order events.
  • Experience with streaming or near-real-time pipelines using Structured Streaming, Kafka, or Auto Loader.
  • Strong observability practices for data systems, including metrics, lineage, data contracts, and incident postmortems.
  • Experience optimizing Databricks cost and performance through cluster sizing, job tuning, Photon, and caching strategies.
  • Experience building governed data products for multi-tenant consumption, including role-based access control, personally identifiable information handling, and auditability.
  • Exposure to healthcare, life sciences, or market research data and related compliance considerations.

About the Company

Konovo

Connects healthcare audiences with real-time insights

Konovo connects market research agencies and consultancies with healthcare professionals through a platform that provides real-time, tech-enabled data and insights. The platform-as-a-service gives clients direct access to engaged healthcare audiences, helping them quickly anticipate market trends and make informed business decisions. Konovo differentiates itself by focusing specifically on healthcare insights and delivering real-time access to credible professional audiences, tuned to broader business objectives. The company's goal is to be a leading platform in healthcare insights, enabling clients to access credible data and actionable intelligence to drive decision-making.

Company size
Not listed
Company stage
Not listed
Total funding
Not listed
Headquarters
Watertown, MA
Founded
Not listed

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