{"schemaVersion":"jobsearcher.job.v1","id":"07a21a512ee508f537e3b520","url":"https://jobsearcher.com/jobs/07a21a512ee508f537e3b520","canonicalUrl":"https://jobsearcher.com/jobs/07a21a512ee508f537e3b520","title":"Data Engineer","description":"Position: Data EngineerDuration: 3 Months with extensionLocation: Montgomery, AL (Onsite from day 1)Job DescriptionIn summary: A Data Quality Engineer, strong data analyst with deep technical skills in SQL, Purview, Data Pipelines and Data Modeling, plus experience in cloud data environments, automated testing, and collaboration with analytics and engineering teams. Ensures data is not only clean but also ready to support advanced analytics and AI applicationsResponsibilitiesData Quality Engineer & Analytics SkillsData Profiling & Cleansing: Analyze data to identify anomalies, duplicates, outliers, and missing values; apply cleansing techniques to improve data integrity.SQL Proficiency: Write complex queries to validate data accuracy, perform transformations, and generate reports. (SSIS - ETL\\ELT)Python & Other Languages: Python is widely used for automation, data validation, and integration with analytics pipelines; SQL is essential for querying and reporting.Data Modeling & Warehousing: Understand ETL/ELT processes, data warehouse/lake/lakehouse architectures, and data modeling principles.Cloud & Modern Data Stack: Experience with cloud platforms (AWS, GCP, Azure), modern data warehouses (Snowflake, BigQuery), and tools like Spark, Kafka/Kinesis, Hadoop, or S3.Data Testing & Observability: Design and deploy automated data testing at scale; use observability platforms for real-time monitoring.Analytics & Data Science SkillsData Quality Standards & Metrics: Define and enforce data quality benchmarks; measure completeness, accuracy, timeliness, and consistency.Root Cause Analysis: Identify why data issues occur (ETL bugs, user input errors, system failures) and implement fixes.Collaboration with Data Scientists: Work with ML/data science teams to ensure training data is clean and reliable.Statistical & Trend Analysis: Interpret patterns in large datasets to inform quality improvements.Soft & Communication SkillsStakeholder Engagement: Gather requirements from business, engineering, and analytics teams; advocate for data quality across the organization.Problem-Solving & Attention to Detail: Spot and resolve data issues efficiently; maintain high precision in validation.Documentation: Record quality issues, processes, and improvements for transparency and compliance.Tools & PlatformsQuery & Analysis: SQL, Python, Spark, Kafka/Kinesis, Hadoop, S3.Data Quality Tools: Data profiling tools (MS Purview), validation scripts, observability platforms.Collaboration: Jira, Snowflake, or other data governance platforms.Required SkillsStrong experience working in low or immature data environments, establishing data quality processes from scratch (8-10 Years)Advanced SQL expertise for complex querying, data validation, and transformation (8-10 Years) Hands-on experience with ETL/ELT pipelines (e.g., SSIS or similar tools) (8-10 Years)Proficiency in Python for data automation, validation, and pipeline integration (5-8 Years)Experience with data profiling and cleansing (anomalies, duplicates, outliers, missing values) (8-10 Years) Solid understanding of data modeling and data warehouse/lake/lakehouse architectures (8-10 Years)Experience implementing data quality frameworks and metrics (accuracy, completeness, timeliness, consistency) (8-10 Years) Experience with cloud data platforms (AWS, Azure, or GCP) and modern data warehouses (e.g., Snowflake, BigQuery) (5-8 Years)Required Tools & Platforms: (8-10 Years) Query & Analysis: SQL, Python, Spark, Kafka/Kinesis, Hadoop, S3. Data Quality Tools: Data profiling tools (MS Purview), validation scripts, observability platforms. Collaboration: Jira, Snowflake, or other data governance platformsPreferred SkillsKnowledge of DAMA-DMBoK, DCAM, MDM concepts, and governance frameworks. (8-10 Years)Experience with Microsoft Purview, Fabric, MS Power BI, and Key Vault (5-8 Years)Familiarity with AI/ML data readiness and feature-store-aligned data structuring. (5-8 Years) Cloud data engineering exposure (Azure, Databricks, GCP). (5-8 Years)Master's Degree Preferred.Certification :- DAMA CDMP (Associate/Practitioner) EDM Council DCAM ASQ Data Quality Credential Collibra Data Steward Certification Certified Data Steward (eLearningCurve) Cloud/AI certifications (Azure, Databricks, Google)","company":"Technix","rawCompany":"technix","city":"Montgomery","state":"AL","isRemote":false,"isActive":false,"createdAt":"2026-06-05T11:31:26.772Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"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":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer","description":"Position: Data EngineerDuration: 3 Months with extensionLocation: Montgomery, AL (Onsite from day 1)Job DescriptionIn summary: A Data Quality Engineer, strong data analyst with deep technical skills in SQL, Purview, Data Pipelines and Data Modeling, plus experience in cloud data environments, automated testing, and collaboration with analytics and engineering teams. Ensures data is not only clean but also ready to support advanced analytics and AI applicationsResponsibilitiesData Quality Engineer & Analytics SkillsData Profiling & Cleansing: Analyze data to identify anomalies, duplicates, outliers, and missing values; apply cleansing techniques to improve data integrity.SQL Proficiency: Write complex queries to validate data accuracy, perform transformations, and generate reports. (SSIS - ETL\\ELT)Python & Other Languages: Python is widely used for automation, data validation, and integration with analytics pipelines; SQL is essential for querying and reporting.Data Modeling & Warehousing: Understand ETL/ELT processes, data warehouse/lake/lakehouse architectures, and data modeling principles.Cloud & Modern Data Stack: Experience with cloud platforms (AWS, GCP, Azure), modern data warehouses (Snowflake, BigQuery), and tools like Spark, Kafka/Kinesis, Hadoop, or S3.Data Testing & Observability: Design and deploy automated data testing at scale; use observability platforms for real-time monitoring.Analytics & Data Science SkillsData Quality Standards & Metrics: Define and enforce data quality benchmarks; measure completeness, accuracy, timeliness, and consistency.Root Cause Analysis: Identify why data issues occur (ETL bugs, user input errors, system failures) and implement fixes.Collaboration with Data Scientists: Work with ML/data science teams to ensure training data is clean and reliable.Statistical & Trend Analysis: Interpret patterns in large datasets to inform quality improvements.Soft & Communication SkillsStakeholder Engagement: Gather requirements from business, engineering, and analytics teams; advocate for data quality across the organization.Problem-Solving & Attention to Detail: Spot and resolve data issues efficiently; maintain high precision in validation.Documentation: Record quality issues, processes, and improvements for transparency and compliance.Tools & PlatformsQuery & Analysis: SQL, Python, Spark, Kafka/Kinesis, Hadoop, S3.Data Quality Tools: Data profiling tools (MS Purview), validation scripts, observability platforms.Collaboration: Jira, Snowflake, or other data governance platforms.Required SkillsStrong experience working in low or immature data environments, establishing data quality processes from scratch (8-10 Years)Advanced SQL expertise for complex querying, data validation, and transformation (8-10 Years) Hands-on experience with ETL/ELT pipelines (e.g., SSIS or similar tools) (8-10 Years)Proficiency in Python for data automation, validation, and pipeline integration (5-8 Years)Experience with data profiling and cleansing (anomalies, duplicates, outliers, missing values) (8-10 Years) Solid understanding of data modeling and data warehouse/lake/lakehouse architectures (8-10 Years)Experience implementing data quality frameworks and metrics (accuracy, completeness, timeliness, consistency) (8-10 Years) Experience with cloud data platforms (AWS, Azure, or GCP) and modern data warehouses (e.g., Snowflake, BigQuery) (5-8 Years)Required Tools & Platforms: (8-10 Years) Query & Analysis: SQL, Python, Spark, Kafka/Kinesis, Hadoop, S3. Data Quality Tools: Data profiling tools (MS Purview), validation scripts, observability platforms. Collaboration: Jira, Snowflake, or other data governance platformsPreferred SkillsKnowledge of DAMA-DMBoK, DCAM, MDM concepts, and governance frameworks. (8-10 Years)Experience with Microsoft Purview, Fabric, MS Power BI, and Key Vault (5-8 Years)Familiarity with AI/ML data readiness and feature-store-aligned data structuring. (5-8 Years) Cloud data engineering exposure (Azure, Databricks, GCP). (5-8 Years)Master's Degree Preferred.Certification :- DAMA CDMP (Associate/Practitioner) EDM Council DCAM ASQ Data Quality Credential Collibra Data Steward Certification Certified Data Steward (eLearningCurve) Cloud/AI certifications (Azure, Databricks, Google)","datePosted":"2026-06-05T11:31:26.772Z","dateModified":"2026-06-05T11:31:26.772Z","hiringOrganization":{"@type":"Organization","name":"Technix","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Montgomery","addressRegion":"AL","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"07a21a512ee508f537e3b520"},"url":"https://jobsearcher.com/jobs/07a21a512ee508f537e3b520"}}