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Wissen Technology

Senior Data Engineer- Snowflake

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Wissen Technology is Hiring for<\/b> <\/b><\/span><\/span><\/span><\/span><\/span>Senior Data Engineer<\/b><\/span><\/span> \-<\/b>Snowflake<\/b><\/span><\/span><\/span>
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About Wissen Technology: <\/b><\/span><\/span><\/span><\/span> <\/b><\/span><\/span><\/span>
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At Wissen Technology, we deliver niche, custom\-built products that solve complex business challenges across industries worldwide. Founded in 2015, our core philosophy is built around a strong product engineering mindset\u2014ensuring every solution is architected and delivered right the first time. Today, Wissen Technology has a global footprint with <\/span><\/span>2000+ employees<\/span> <\/span>across offices in the<\/span> <\/span>US, UK, UAE, India, <\/span><\/span>and <\/span><\/span>Australia<\/span>. Our commitment to excellence translates into delivering <\/span><\/span>2X<\/span> <\/span>impact compared to traditional service providers. How do we achieve this? Through a combination of deep domain knowledge, <\/span><\/span>cutting\-edge<\/span> <\/span>technology <\/span><\/span>expertise<\/span>, and a relentless focus on quality. We <\/span><\/span>don\u2019t<\/span> <\/span>just meet expectations\u2014we exceed them by ensuring faster time\-to\-market, reduced rework, and greater alignment with client <\/span><\/span>objectives<\/span>. We have a proven <\/span><\/span>track record<\/span> <\/span>of building mission\-critical systems across industries, including financial services, healthcare, retail, manufacturing, and more. Wissen stands apart through its unique delivery models. Our outcome\-based projects ensure predictable costs and timelines, while our agile pods <\/span><\/span>provide<\/span> <\/span><\/span>clients with<\/span> <\/span>the flexibility to adapt to their evolving business needs. Wissen leverages its thought leadership and technology prowess to drive superior business outcomes. Our success is powered by top\-tier t<\/span>ale<\/span>nt<\/span>. <\/span><\/span>Our mission is clear: to be the partner of choice for building world\-class custom products that deliver exceptional impact\u2014the first time, every time.<\/span><\/span><\/span><\/span> <\/span><\/span><\/span>
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Job Summary<\/b><\/span>:<\/b><\/span><\/span><\/span> <\/span><\/span>We are looking for an experienced Data Engineer to join our data platform team to support the migration of a legacy Data Lake architecture to a modern Lakehouse architecture. The role involves designing and building scalable data pipelines using Apache Spark, Refiner frameworks, and other AWS cloud\-native data engineering tools, while integrating with Snowflake for advanced analytics and data warehousing.<\/span><\/span><\/span> <\/span><\/span>
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The ideal candidate will have strong experience in distributed data processing, cloud data platforms, and large\-scale data migration projects.<\/span><\/span><\/span> <\/span><\/span>
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Experience:<\/b> 6<\/span><\/span><\/span>\-<\/span> <\/span>12<\/span> y<\/span><\/span><\/span>ear<\/span>s<\/span><\/span><\/span><\/span> <\/span><\/span><\/span>
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Location:<\/b><\/span><\/span><\/span> <\/span><\/span><\/span><\/span><\/span> <\/span>Bangalore<\/span><\/span><\/span><\/span> <\/span><\/span><\/span>
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Mode of Work<\/b><\/span>:<\/b><\/span> <\/span><\/span><\/span><\/span>Full time<\/span> <\/span><\/span><\/span> <\/span><\/span>
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Key<\/b> <\/b><\/span><\/span>Responsibilities:<\/b><\/span><\/span><\/span> <\/b><\/span><\/span>
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  • Design and implement data pipelines to migrate data from existing Data Lake to Lakehouse architecture.<\/span><\/span><\/span> <\/span><\/span>
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  • Develop and <\/span>optimize <\/span>Spark\-based ETL/ELT pipelines using Spark Refiner or similar transformation frameworks.<\/span><\/span><\/span> <\/span><\/span>
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  • Build scalable data processing workflows using AWS services such as S3, Glue, EMR, Lambda, and Step Functions.<\/span><\/span><\/span> <\/span><\/span>
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  • Integrate and manage data ingestion into Snowflake for analytics and downstream consumption.<\/span><\/span><\/span> <\/span><\/span>
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  • Perform data modelling for Lakehouse architecture (Bronze, Silver, Gold layers).<\/span><\/span><\/span> <\/span><\/span>
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  • Ensure data quality, governance, and lineage across the migration process.<\/span><\/span><\/span> <\/span><\/span>
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  • Optimize <\/span>performance of Spark jobs and Snowflake queries for large\-scale datasets.<\/span><\/span><\/span> <\/span><\/span>
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  • Work closely with data architects, analytics teams, and business stakeholders to ensure reliable data delivery.<\/span><\/span><\/span> <\/span><\/span>
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  • Implement CI/CD pipelines for data engineering workflows.<\/span><\/span><\/span> <\/span><\/span>
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  • Support data validation, reconciliation, and testing during migration.<\/span><\/span><\/span> <\/span><\/span>
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    Requirements:<\/b><\/span><\/span><\/span> <\/b><\/span><\/span>
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    • Strong experience with <\/span>Apache Spark (<\/span>PySpark<\/span> <\/span>/ Scala)<\/span><\/span><\/span> <\/span><\/span>
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    • Experience with <\/span>Spark Refiner <\/span>or similar transformation frameworks<\/span><\/span><\/span> <\/span><\/span>
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    • Hands\-on <\/span>expertise <\/span>with <\/span>AWS Data Ecosystem, including: <\/span><\/span><\/span><\/span> <\/span><\/span>
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    • S3, Glue, EMR, Lambda, Step Functions, IAM<\/span><\/span><\/span> <\/span><\/span>
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    • Experience building large\-scale <\/span>ETL/ELT pipelines<\/span><\/span><\/span> <\/span><\/span>
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    • Strong knowledge of <\/span>Snowflake, including: <\/span><\/span><\/span><\/span> <\/span><\/span>
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    • Snowpipe<\/span><\/span><\/span> <\/span><\/span>
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    • Data loading<\/span><\/span><\/span> <\/span><\/span>
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    • Performance optimization<\/span><\/span><\/span> <\/span><\/span>
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    • Excellent <\/span>SQL <\/span>and <\/span>data modelling <\/span>skills<\/span><\/span><\/span> <\/span><\/span>
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    • Understanding of <\/span>Data Lake, Lakehouse architectures, and modern data storage formats<\/span><\/span><\/span> <\/span><\/span>
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    • Knowledge of <\/span>data migration strategies <\/span>and validation techniques<\/span><\/span><\/span> <\/span><\/span><\/span>
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      Good To Have Sk<\/b><\/span>ills:<\/b><\/span> <\/b><\/span><\/span><\/span><\/span> <\/b><\/span><\/span><\/span>
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      • Experience with <\/span>Delta Lake, Iceberg, or Hudi<\/span><\/span><\/span> <\/span><\/span>
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      • Familiarity with <\/span>Airflow <\/span>or other workflow orchestration tools<\/span><\/span><\/span> <\/span><\/span>
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      • Knowledge of <\/span>DevOps practices <\/span>and CI/CD tools<\/span><\/span><\/span> <\/span><\/span>
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      • Experience with <\/span>data governance <\/span>and <\/span><\/span>catalog<\/span> <\/span>tooling<\/span><\/span><\/span> <\/span><\/span>
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      • Exposure to streaming platforms such as <\/span><\/span>Kafka<\/span> <\/span>or <\/span><\/span>Kinesis<\/span><\/span><\/span> <\/span><\/span><\/span>
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        Wissen Sites:<\/b><\/span><\/span><\/span><\/span> <\/b><\/span><\/span><\/span>
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        Website: <\/span><\/span><\/span><\/span>www.wissen.com<\/span><\/u><\/span><\/span><\/span><\/a> <\/span><\/span><\/span> <\/span><\/span>
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        LinkedIn: <\/span><\/span><\/span><\/span>https://www.linkedin.com/company/wissen\-technology<\/span><\/u><\/span><\/span><\/span><\/a> <\/span><\/span><\/span> <\/span><\/span>
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        Wissen Leadership: <\/span><\/span><\/span><\/span>https://www.wissen.com/company/leadership\-team/<\/span><\/u><\/span><\/span><\/span><\/a> <\/span><\/span><\/span> <\/span><\/span>
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