{"id":3833750,"url":"https://alion.io/job/narwal-sr-data-engineer","title":"Sr Data Engineer","company":{"id":59137,"name":"Narwal","domain":"narwal.com","url":"https://alion.io/company/narwal","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"dbt","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Fivetran","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Incident Management","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-11-05T17:27:02Z","employer_posted_date":null,"last_verified_at":"2026-11-05T17:27:02Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"About Us:\nNarwal, with its Global Delivery Model, strategically expands its reach across North America, the United Kingdom, and an offshore development centre in India. Delivery cutting edge AI, Data and Quality Engineering solutions and consistently surpassing expectations, Narwal has achieved remarkable triple-digit growth rates year after year, earning accolades such as Inc. 5000, Best IT Services Company, Best Data Technology Company, and Partner of the Year with Tricentis. \n\nOur Vision:\nTo be an expert in AI, Data and Quality Engineering transformations, bold in our thinking and authentic in our relationships.\n\nTitle: Sr Data Engineer\nExperience Level : 6-12 years\nMust Have Skills - Snowflake, DBT, AWS OR GCP, Airflow, Kafka, Fivetran\nWork Location- Pune ( Work from Office)\n\nAbout the Role\nWe are looking for an experienced Data Engineer with 6+ years of hands-on experience in designing, developing, and operationalizing enterprise data ingestion pipelines and trusted data products within a Data Lake ecosystem. The ideal candidate will have strong experience across data ingestion, transformation, orchestration, data governance, data quality, and production operations. The role requires hands-on expertise with technologies such as Fivetran, Kafka, Apache Iceberg, Snowflake, dbt, and Astronomer/Airflow, along with exposure to data observability using Monte Carlo.\nKey Responsibilities\nLead the design, development, and implementation of enterprise data ingestion initiatives using Fivetran, Kafka, and Apache Iceberg.\nDesign and build scalable, reliable batch and near-real-time ingestion pipelines to integrate data from diverse source systems into the Data Lake ecosystem.\nDevelop and maintain ingestion frameworks and data pipelines, ensuring performance, scalability, and operational reliability.\nBuild and optimize data transformation pipelines using dbt, following modularity, reusability, testing, and documentation best practices.\nBuild, schedule, monitor, and troubleshoot workflows using Apache Airflow and Astronomer.\nDevelop reusable and modular Airflow DAGs and support the management and operation of Airflow environments.\nDevelop and maintain Trusted Data Layer assets, ensuring data is validated, consistent, and ready for downstream consumption.\nPublish curated datasets to Snowflake and support efficient data models for analytics and other downstream use cases.\nPartner with stakeholders to implement data cataloging, classification, metadata management, lineage, and other data governance requirements.\nImplement data quality tests, validation rules, and reconciliation mechanisms to ensure data accuracy, consistency, and reliability.\nConfigure, implement, and maintain Monte Carlo for data observability, monitoring, anomaly detection, and alerting.\nMonitor pipeline health, proactively identify data quality or pipeline issues, and drive timely resolution.\nCollaborate with SRE teams to support production operations, incident management, root cause analysis, and platform reliability.\nImplement appropriate logging, alerting, error handling, and recovery mechanisms for production-grade data pipelines.\nDocument technical solutions, data workflows, operational procedures, and provide technical leadership throughout the delivery lifecycle.\nMust-Have Skills\n6+ years of overall experience in Data Engineering, with hands-on experience building and supporting production-grade data pipelines.\nStrong hands-on experience with Fivetran for data ingestion and integration from multiple source systems.\nExperience with Apache Kafka for event-driven and near-real-time data ingestion.\nHands-on experience with Apache Iceberg and a good understanding of open table formats and Data Lake/Lakehouse concepts.\nStrong hands-on experience with Snowflake, including data modeling and publishing curated datasets.\nStrong hands-on experience with dbt for data transformation, models, tests, and documentation.\nStrong experience with Apache Airflow for workflow orchestration and DAG development.\nExperience working with Astronomer and managing or operating Airflow environments.\nExperience with Monte Carlo for data observability, monitoring, anomaly detection, and alerting.\nGood understanding of data governance concepts, including data cataloging, classification, metadata management, and lineage.\nExperience implementing data quality checks, validation, and testing frameworks.\nExperience supporting production data platforms, troubleshooting pipeline failures, and participating in incident resolution.\nStrong SQL skills and understanding of ETL/ELT, data integration, and data modeling concepts.\nExperience with Git, version control, code reviews, and standard software engineering practices.\nExposure to cloud platforms such as Google Cloud Platform (GCP) or Amazon Web Services (AWS) is preferred.\nEducation\nBachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.\nEquivalent technical experience may also be 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