{"schemaVersion":"jobsearcher.job.v1","id":"f5f07ffecc8838176cbbb8fe","url":"https://jobsearcher.com/jobs/f5f07ffecc8838176cbbb8fe","canonicalUrl":"https://jobsearcher.com/jobs/f5f07ffecc8838176cbbb8fe","title":"Data Engineer","description":"Blutic is seeking a skilled Data Engineer with 5+ years of experience with strong hands-on experience in pipeline migration, consumption pattern migration, data reconciliation, and quality validation. The ideal candidate should have practical experience working with Snowflake, Apache Iceberg, Spark, Kafka, SQL, and large-scale data engineering platforms, along with strong understanding of SDLC, CI/CD, and data modeling concepts.This is a full time opportunity.Job LocationDallas, TXEmployment TypeFull Time / HybridExperience5+ YearsKey Responsibilities· Pipeline Migration – Refactoring and migrating extraction logic and job scheduling from legacy frameworks to the new Lakehouse environment.· Pipeline Migration – Executing the physical migration of underlying datasets while ensuring data integrity.· Pipeline Migration – Acting as a technical liaison to internal clients, facilitating handoff and sign-off conversations with data owners to ensure migrated assets meet business requirements.· Consumption Pattern Migration – Translating and optimizing legacy SQL and Spark-based consumption patterns (raw and modeled) for compatibility with Snowflake and Iceberg.· Consumption Pattern Migration – Understand usage patterns to deliver the required data products.· Consumption Pattern Migration – Acting as a technical liaison to internal clients, facilitating handoff and sign-off conversations with data owners to ensure migrated assets meet business requirements.· Data Reconciliation & Quality – Work with reconciliation frameworks to build confidence that migrated data is functionally equivalent to that already used within production flows. Technical Skills:Experience: Minimum of 5 years of professional \"hands-on-keyboard\" coding experience in a collaborative, team-based environment. Ability to trouble shoot (SQL) and basic scripting experience.Languages: Professional proficiency in Python or Java.Methodology: Deep familiarity with the full Software Development Life Cycle (SDLC) and CI/CD best practices & K8s deployment experience.Core Data Engineering Competencies: Candidates must demonstrate a sophisticated understanding of the following modeling concepts to ensure data correctness during reconciliation:Temporal Data Modeling: Managing state changes over time (e.g., SCD Type 2).Schema Management: Expertise in Schema Evolution (Ref: Iceberg Apache) and enforcement strategies.Performance Optimization: Advanced knowledge of data partitioning and clustering.Architectural Theory: Balancing Normalization vs. Denormalization and the strategic use of Natural vs. Surrogate Keys.Technical Stack Requirements: Extraction & Logic: Kafka, ANSI SQL, FTP, Apache SparkData Formats: JSON, Avro, ParquetPlatforms: Hadoop (HDFS/Hive), Snowflake, Apache Iceberg, Sybase IQCandidate will also need to work with our internal data management platform, and must have an aptitude for learning new workflows and language constructs is essential.","company":"Blutic","rawCompany":"blutic","city":"Dallas","state":"TX","isRemote":false,"isActive":false,"createdAt":"2026-05-31T00:13:33.839Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"}],"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":"Blutic is seeking a skilled Data Engineer with 5+ years of experience with strong hands-on experience in pipeline migration, consumption pattern migration, data reconciliation, and quality validation. The ideal candidate should have practical experience working with Snowflake, Apache Iceberg, Spark, Kafka, SQL, and large-scale data engineering platforms, along with strong understanding of SDLC, CI/CD, and data modeling concepts.This is a full time opportunity.Job LocationDallas, TXEmployment TypeFull Time / HybridExperience5+ YearsKey Responsibilities· Pipeline Migration – Refactoring and migrating extraction logic and job scheduling from legacy frameworks to the new Lakehouse environment.· Pipeline Migration – Executing the physical migration of underlying datasets while ensuring data integrity.· Pipeline Migration – Acting as a technical liaison to internal clients, facilitating handoff and sign-off conversations with data owners to ensure migrated assets meet business requirements.· Consumption Pattern Migration – Translating and optimizing legacy SQL and Spark-based consumption patterns (raw and modeled) for compatibility with Snowflake and Iceberg.· Consumption Pattern Migration – Understand usage patterns to deliver the required data products.· Consumption Pattern Migration – Acting as a technical liaison to internal clients, facilitating handoff and sign-off conversations with data owners to ensure migrated assets meet business requirements.· Data Reconciliation & Quality – Work with reconciliation frameworks to build confidence that migrated data is functionally equivalent to that already used within production flows. Technical Skills:Experience: Minimum of 5 years of professional \"hands-on-keyboard\" coding experience in a collaborative, team-based environment. Ability to trouble shoot (SQL) and basic scripting experience.Languages: Professional proficiency in Python or Java.Methodology: Deep familiarity with the full Software Development Life Cycle (SDLC) and CI/CD best practices & K8s deployment experience.Core Data Engineering Competencies: Candidates must demonstrate a sophisticated understanding of the following modeling concepts to ensure data correctness during reconciliation:Temporal Data Modeling: Managing state changes over time (e.g., SCD Type 2).Schema Management: Expertise in Schema Evolution (Ref: Iceberg Apache) and enforcement strategies.Performance Optimization: Advanced knowledge of data partitioning and clustering.Architectural Theory: Balancing Normalization vs. Denormalization and the strategic use of Natural vs. Surrogate Keys.Technical Stack Requirements: Extraction & Logic: Kafka, ANSI SQL, FTP, Apache SparkData Formats: JSON, Avro, ParquetPlatforms: Hadoop (HDFS/Hive), Snowflake, Apache Iceberg, Sybase IQCandidate will also need to work with our internal data management platform, and must have an aptitude for learning new workflows and language constructs is essential.","datePosted":"2026-05-31T00:13:33.839Z","dateModified":"2026-05-31T00:13:33.839Z","hiringOrganization":{"@type":"Organization","name":"Blutic","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Dallas","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"f5f07ffecc8838176cbbb8fe"},"url":"https://jobsearcher.com/jobs/f5f07ffecc8838176cbbb8fe"}}