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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** Kls Martin Lp - **Location:** Jacksonville, FL, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Amazon S3, Data Analysis, Software Applications, Microsoft Azure, Big Data, Cloud Computing, Cloud Database, Data Architecture, Data Validation, Data Cleansing, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Retrieval, Data Systems, Data Warehousing, DevOps, Dimensional Modeling, Fault Tolerance, Data Flow Control, Information Extraction, Python (Programming Language), Meta-Data Management, Microsoft SQL Server, MongoDB, MySQL, Online Analytical Processing, Natural Language Processing, NoSQL, Online Transaction Processing, Performance Tuning, Query Optimization, Role-Based Access Control, Power BI, Cloud Services, Standard Sql, Software Engineering, SQL Databases, Tableau (Software), Talend, Unstructured Data, User-Centered Design, Data Logging, Data Processing, Freeform SQL, Software Modules, Real Time Systems, Feature Engineering, Informatica Powercenter, Snowflake, Caching, Database Performance, Indexer, Event Driven Architecture, Microsoft Fabric, Data Lineage, Cassandra, Data Analytics, Star Schema, Google Bigquery, Apache Kafka, Data Management, Physical Data Models, Restful APIs, Azure Synapse Analytics, Looker Analytics, Data Pipelines, Amazon Redshift - **Published:** June 3, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=7b464e799ea8089d ## About the Role Do you have experience in Typing?, Do you have a Bachelor's degree?, * Bachelor's degree and 6+ years of experience in data analytics, data engineering, data architecture, or software engineering with a focus on data warehouse design and implementation. * Proven experience designing and implementing dimensional data models (star schema, snowflake schema) for enterprise-scale data warehouses. * Hands-on experience with ETL/ELT development using tools like dbt, Informatica, Talend, Apache Airflow, or custom data pipelines. * 3+ years of experience working with cloud-based data warehouse platforms such as Snowflake, AWS Redshift, Google BigQuery, or Azure Synapse Analytics. * Strong knowledge of SQL, Python, and/or Scala for data processing and transformation. * Experience with relational and (preferably) NoSQL databases (e.g., SQL Server, MySQL, MongoDB, Cassandra). * Experience with Microsoft Fabric/Synapse/OneLake preferred. * Experience implementing data governance, data quality frameworks, and role-based access control (RBAC). * Experience working closely with other departments and teams to ensure alignment on goals and objectives for successful project execution. * Perform work under minimal supervision. Experience with understanding data requirements and performing data preparation and feature engineering tasks to support model training and evaluation preferred. Knowledge, Skills, and Abilities * Identify areas of improvement, troubleshoot issues, and propose creative solutions that drive efficiency and better business results. * Continuously assess and refine internal processes to enhance team productivity and reduce bottlenecks. * Able to assess complex problems, weigh options, and devise practical solutions. * Handle complex issues and problems and refers only the most complex issues to higher-level staff. * Deep understanding of dimensional modeling (star and snowflake schemas), OLAP vs. OLTP, and modern data warehouse design principles. * In-depth knowledge of ETL/ELT best practices, incremental data processing, and tools like dbt, Apache Airflow, Informatica, Talend, Fivetran. * Understanding of data governance frameworks, data lineage, metadata management, role-based access control (RBAC), and compliance regulations (GDPR, HIPAA, CCPA). * Knowledge of query tuning, indexing, partitioning, caching strategies, and workload optimization for large-scale data warehouses. * Regularly update and communicate project status, timelines, and risks to both internal and external stakeholders. * Ability to write optimized, complex SQL queries for data retrieval, transformation, and aggregation. * Hands-on experience building scalable, fault-tolerant data pipelines for batch and real-time processing. * Experience with RESTful APIs, event-driven architecture (Kafka, Pub/Sub), and integrating third-party data sources. * Practical experience deploying and managing data solutions on AWS (S3, Glue, Lambda), GCP (Dataflow, Pub/Sub), or Azure (Data Factory, Synapse Analytics). * Familiarity with BI tools (Tableau, Looker, Power BI, Mode Analytics) and self-service analytics enablement. * Design and implement high-performance, resilient, and cost-effective data architectures. * Analyze and resolve data integrity, scalability, and pipeline failures with structured problem-solving. * Provide leadership, coaching, and/or mentoring to foster growth in the team. * Explain technical concepts to non-technical stakeholders and advocate for data-driven decision-making. * Stay current with evolving data engineering trends, tools, and methodologies. Skill Requirements * Typing/computer keyboard * Utilize computer software (specified above) * Retrieve and compile information * Verify data and information * Organize and prioritize information/tasks * Advanced mathematical concepts (fractions, decimals, ratios, percentages, graphs) * Verbal communication * Written communication * Research, analyze and interpret information * Investigate, evaluate, recommend action ## Description This position will lead the design, evaluation, implementation, and testing of a scalable, high-performance enterprise data warehouse. In this role, you will be responsible for developing dimensional data models, ETL/ELT pipelines, and cloud-based data solutions that enable robust analytics and reporting. You will collaborate with cross-functional teams to ensure data quality, governance, and security while optimizing performance for large-scale datasets. The ideal candidate has a strong background in SQL, cloud data platforms (AWS, GCP, or Azure), and data pipeline automation and is enthusiastic about building modern data architectures and enabling data-driven decision-making., * Data Warehouse Design & Architecture + Lead the end-to-end design and implementation of a scalable, high-performance data warehouse. + Define data architecture principles, strategies, and best practices to ensure optimal performance and maintainability. * Dimensional Modeling & Data Modeling + Design and implement robust dimensional models (star and snowflake schemas) to optimize analytical queries. + Develop conceptual, logical, and physical data models to support reporting, analytics, and business intelligence (BI). + Ensure data models align with business requirements and support self-service analytics. + Leverages existing data infrastructure to fulfill all data-related requests, perform necessary data housekeeping, data cleansing, normalization, hashing, and implementation of required data model changes. * ETL/ELT Development & Data Pipelines + Design, develop, and optimize ETL/ELT pipelines to ingest, transform, and load structured and unstructured data from various sources. + Ensure data pipelines are scalable, efficient, and maintainable while handling large datasets. + Implement incremental data processing strategies to manage real-time and batch workloads. * Data Governance, Quality, and Security + Establish data governance practices, including data cataloging, lineage tracking, and metadata management. + Implement data validation, anomaly detection, and quality monitoring to ensure accuracy and consistency. + Collaborate with security teams to enforce role-based access control (RBAC), encryption, and compliance standards (GDPR, HIPAA, etc.). * Performance Tuning & Optimization + Optimize database performance by indexing, partitioning, caching, and query tuning. + Monitor and troubleshoot slow queries, ensuring efficient use of resources. + Analyze data to spot anomalies, trends and correlate similar data sets. * Cloud Technologies + Architect and implement cloud-based data warehouse solutions (e.g., Snowflake, AWS Redshift, Google BigQuery, Azure Synapse). * Collaboration & Cross-Functional Work + Work closely with business stakeholders & analysts to translate requirements into scalable data solutions. + Partner with software engineers and DevOps teams to ensure seamless data integration and infrastructure reliability. * Monitoring & Incident Response + Establish monitoring solutions for data pipeline failures, schema changes, and data anomalies. + Set up logging and alerting mechanisms to proactively identify and resolve issues. * Mentorship & Best Practices + Guide and mentor other members of the data team on best practices in data modeling, ETL, and architecture. + Define and document standards for data warehouse development, maintenance, and governance. * Data Science & Machine Learning + Designs, develops, and implements statistical models to carry out various novel aspects of classification and information extraction from data. + Designs, develops, and implements natural language processing software modules., * Reading * Speaking * Hear/Listen * Maintain regular, punctual attendance * Pushing/Pulling * Bending/Stooping * Reaching/Grasping * Writing ## Related Videos - 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