{"schemaVersion":"jobsearcher.job.v1","id":"2b99ba99fa24fad04f1f07ee","url":"https://jobsearcher.com/jobs/2b99ba99fa24fad04f1f07ee","canonicalUrl":"https://jobsearcher.com/jobs/2b99ba99fa24fad04f1f07ee","title":"Data Engineer","description":"Title: Data Engineer\r\nLocation : Columbus, IN.\r\nAbout the Role\r\nWe are hiring a Data Engineer with strong hands-on experience in building\r\nhigh-performance data pipelines for a heavy data analytics project. The candidate must beexcellent at writing complex aggregations, understanding business processes and analyticalrequirements, and designing scalable data lake and data warehouse solutions. Experienceacross multiple data platforms (Databricks, Snowflake, Azure Data Factory, Synapse, etc.) isa strong advantage.\r\nKey Responsibilities\r\n1. Data Pipeline & ETL/ELT DevelopmentDevelop, optimize, and productionize Spark (PySpark/Scala) pipelines.\r\nIngest, transform, cleanse, and aggregate large datasets from varied sources.\r\nImplement scalable ETL/ELT logic for batch and near-real-time pipelines.\r\nApply best practices in partitioning, caching, Delta Lake optimization, and performancetuning.\r\n2. Heavy Data Analytics & Business UnderstandingWrite complex aggregation logic (window functions, rollups, grouping sets, analytical\r\nfunctions).\r\nUnderstand business KPIs, metrics, and analytical use cases.\r\nTranslate business needs into technical transformations and data models.\r\nValidate data outputs against business logic and analytics expectations.\r\nCollaborate with analysts on calculations: weekly/monthly aggregates, trend lines,performance metrics, dimensional rollups.\r\nEnsure accuracy, consistency, and traceability of business-critical metrics.\r\n3. Data Lake EngineeringBuild and maintain multi-layer Data Lake architectures (Bronze/Silver/Gold).\r\nWork with Parquet, Delta Lake, ORC, and columnar storage formats.\r\nImplement schema evolution, auditing, and metadata strategies.\r\n4. Data Warehouse EngineeringDesign dimensional models: Star Schema and Snowflake Schema.\r\nBuild fact and dimension tables supporting analytics and reporting.\r\nOptimize table structures, keys, and partitioning strategies.\r\n5. Databricks (Added Advantage)Develop notebooks/jobs using PySpark/Scala.\r\nManage clusters, workflows, and Delta Live Tables.\r\nImplement best practices for performance and cost efficiency.\r\n6. SQL EngineeringStrong command of SQL for aggregations, analytical functions, joins,profiling, andvalidation.\r\nWrite and optimize complex queries supporting dashboards, metrics, and reports.\r\n7. Cloud Data PlatformsAzure: Data Factory, Synapse Analytics, ADLS Gen2, Azure Functions (optional).\r\nSnowflake: Virtual Warehouses, Snowpipe, Streams & Tasks, performance tuning.\r\n8. Data Quality & DocumentationValidate transformation logic against business rules.\r\nDocument data flows, transformation rules, aggregation logic, and data\r\ndictionary/metadata.\r\nWork with QA and analysts to ensure outputs match business expectations.\r\nRequired Qualifications\r\n5+ years of hands-on data engineering experience.\r\nStrong programming skills: Spark, Scala, Python.\r\nStrong SQL skills (aggregations, analytical functions, large joins).\r\nExperience with Data Lake and Data Warehouse concepts.\r\nExperience with Spark-based processing (delta optimization, shuffle tuning, partitioning).\r\nExperience with at least one cloud data ecosystem (Azure/AWS/GCP).\r\nPreferred Skills\r\nExperience with Databricks (highly desirable).\r\nExperience with Snowflake or modern cloud DWH.\r\nExperience with ADF/Synapse/Airflow/dbt for orchestration.\r\nKnowledge of CI/CD for data pipelines.\r\nExperience with large-scale data analytics environments.\r\nSoft Skills\r\nStrong understanding of business logic behind analytics outputs.\r\nAbility to translate business metrics into technical transformations.\r\nStrong problem-solving and debugging skills.\r\nGood communication and cross-team collaboration.\r\nJ-18808-Ljbffr","company":"Dorle Controls","rawCompany":"dorle controls","city":"Columbus","state":"IN","isRemote":false,"isActive":false,"createdAt":"2026-07-16T01:41:59.347Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer","description":"Title: Data Engineer\r\nLocation : Columbus, IN.\r\nAbout the Role\r\nWe are hiring a Data Engineer with strong hands-on experience in building\r\nhigh-performance data pipelines for a heavy data analytics project. The candidate must beexcellent at writing complex aggregations, understanding business processes and analyticalrequirements, and designing scalable data lake and data warehouse solutions. Experienceacross multiple data platforms (Databricks, Snowflake, Azure Data Factory, Synapse, etc.) isa strong advantage.\r\nKey Responsibilities\r\n1. Data Pipeline & ETL/ELT DevelopmentDevelop, optimize, and productionize Spark (PySpark/Scala) pipelines.\r\nIngest, transform, cleanse, and aggregate large datasets from varied sources.\r\nImplement scalable ETL/ELT logic for batch and near-real-time pipelines.\r\nApply best practices in partitioning, caching, Delta Lake optimization, and performancetuning.\r\n2. Heavy Data Analytics & Business UnderstandingWrite complex aggregation logic (window functions, rollups, grouping sets, analytical\r\nfunctions).\r\nUnderstand business KPIs, metrics, and analytical use cases.\r\nTranslate business needs into technical transformations and data models.\r\nValidate data outputs against business logic and analytics expectations.\r\nCollaborate with analysts on calculations: weekly/monthly aggregates, trend lines,performance metrics, dimensional rollups.\r\nEnsure accuracy, consistency, and traceability of business-critical metrics.\r\n3. Data Lake EngineeringBuild and maintain multi-layer Data Lake architectures (Bronze/Silver/Gold).\r\nWork with Parquet, Delta Lake, ORC, and columnar storage formats.\r\nImplement schema evolution, auditing, and metadata strategies.\r\n4. Data Warehouse EngineeringDesign dimensional models: Star Schema and Snowflake Schema.\r\nBuild fact and dimension tables supporting analytics and reporting.\r\nOptimize table structures, keys, and partitioning strategies.\r\n5. Databricks (Added Advantage)Develop notebooks/jobs using PySpark/Scala.\r\nManage clusters, workflows, and Delta Live Tables.\r\nImplement best practices for performance and cost efficiency.\r\n6. SQL EngineeringStrong command of SQL for aggregations, analytical functions, joins,profiling, andvalidation.\r\nWrite and optimize complex queries supporting dashboards, metrics, and reports.\r\n7. Cloud Data PlatformsAzure: Data Factory, Synapse Analytics, ADLS Gen2, Azure Functions (optional).\r\nSnowflake: Virtual Warehouses, Snowpipe, Streams & Tasks, performance tuning.\r\n8. Data Quality & DocumentationValidate transformation logic against business rules.\r\nDocument data flows, transformation rules, aggregation logic, and data\r\ndictionary/metadata.\r\nWork with QA and analysts to ensure outputs match business expectations.\r\nRequired Qualifications\r\n5+ years of hands-on data engineering experience.\r\nStrong programming skills: Spark, Scala, Python.\r\nStrong SQL skills (aggregations, analytical functions, large joins).\r\nExperience with Data Lake and Data Warehouse concepts.\r\nExperience with Spark-based processing (delta optimization, shuffle tuning, partitioning).\r\nExperience with at least one cloud data ecosystem (Azure/AWS/GCP).\r\nPreferred Skills\r\nExperience with Databricks (highly desirable).\r\nExperience with Snowflake or modern cloud DWH.\r\nExperience with ADF/Synapse/Airflow/dbt for orchestration.\r\nKnowledge of CI/CD for data pipelines.\r\nExperience with large-scale data analytics environments.\r\nSoft Skills\r\nStrong understanding of business logic behind analytics outputs.\r\nAbility to translate business metrics into technical transformations.\r\nStrong problem-solving and debugging skills.\r\nGood communication and cross-team collaboration.\r\nJ-18808-Ljbffr","datePosted":"2026-07-16T01:41:59.347Z","dateModified":"2026-07-16T01:41:59.347Z","hiringOrganization":{"@type":"Organization","name":"Dorle Controls","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Columbus","addressRegion":"IN","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"2b99ba99fa24fad04f1f07ee"},"url":"https://jobsearcher.com/jobs/2b99ba99fa24fad04f1f07ee"}}