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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - ETL, Data Pipelines & Big Data - **Company:** Wintrio LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, Batch Processing, Big Data, Cloud Database, Information Systems, Databases, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Security, Data Systems, Data Warehousing, Relational Databases, Database Design, Dimensional Modeling, Distributed Computing Environment, Amazon DynamoDB, Fault Tolerance, Github, Apache Hadoop, JSON, Python (Programming Language), PostgreSQL, Machine Learning, Meta-Data Management, Metadata Repositories, Microsoft SQL Server, MongoDB, MySQL, Oracle Databases, Cloud Services, Prometheus, Standard Sql, Azure Data Lake, SQL Databases, SQL Server Integration Services, Data Streaming, Systems Integration, Talend, Unstructured Data, Extensible Markup Language (XML), Enterprise Data Management, Data Logging, Data Processing, Enterprise Software Applications, Azure Data Factory, Snowflake, Apache Spark, AWS Lambda, HybridCloud, Gitlab, Git, Event Driven Architecture, Data Lakes, Storage Technologies, Information Technology, Data Lineage, Collibra, Apache Flink, AWS Glue, Data Analytics, Star Schema, Enterprise Integration, Apache Kafka, Bitbucket, Data Management, Cloudwatch, Restful APIs, Stream Processing, Azure Synapse Analytics, Software Version Control, Data Pipelines, Serverless Computing, Amazon Redshift, Databricks, Programming Languages, Microservices - **Published:** June 25, 2026 - **Apply:** https://www.wintrio.com/careers/data-engineer-etl-data-pipelines-big-data/ ## About the Role * Bachelor's degree in Computer Science, Data Engineering, Information Technology, Information Systems, Engineering, or a related field. * Minimum five (5) years of experience in Data Engineering, ETL development, data integration, or enterprise data platform engineering. * Strong experience with SQL, relational databases, and data modeling concepts. * Experience working with AWS, Microsoft Azure, or hybrid cloud-based data platforms. * Experience designing and implementing ETL/ELT pipelines using modern data integration frameworks. * Strong understanding of data warehousing, data governance, and enterprise integration concepts. * Strong written and verbal communication skills. * Strong analytical, troubleshooting, and problem-solving abilities. Technical Areas Data Engineering * Data Pipeline Development * ETL/ELT Engineering * Data Integration * Batch Processing * Real-Time Data Processing * Streaming Data * Data Platform Engineering Data Architecture * Data Modeling * Star Schema * Snowflake Schema * Dimensional Modeling * Data Warehousing * Data Lake Architecture * Database Design Big Data & Analytics * Distributed Data Processing * Big Data Platforms * Enterprise Analytics * Data Transformation * Data Optimization * High-Volume Data Processing Cloud Data Platforms * Amazon Web Services (AWS) * Microsoft Azure * Hybrid Cloud Data Platforms * Cloud Data Lakes * Cloud Data Warehouses Data Governance * Data Quality * Metadata Management * Data Lineage * Data Catalog * Data Security * Data Compliance Tools & Platforms Programming Languages * Python * SQL * Scala (Preferred) * Java (Optional) ETL / ELT Platforms * Apache Airflow * Azure Data Factory * AWS Glue * Informatica * Talend * SQL Server Integration Services (SSIS) Big Data Technologies * Apache Spark * Hadoop * Databricks * Apache Kafka * Apache Flink Cloud Data Services * Amazon S3 * Amazon Redshift * AWS Glue * AWS Lambda * Amazon Kinesis * Azure Data Lake * Azure Synapse Analytics * Azure Data Factory * Azure Event Hub Databases * Microsoft SQL Server * PostgreSQL * MySQL * Oracle Database * MongoDB * Amazon DynamoDB Data Warehousing * Snowflake * Amazon Redshift * Azure Synapse Analytics Integration Technologies * REST APIs * JSON * XML * Microservices Integration Data Governance Platforms * Microsoft Purview * Collibra * Alation Monitoring & Operations * Amazon CloudWatch * Azure Monitor * Prometheus * Pipeline Logging Version Control * Git * GitHub * GitLab * Bitbucket Preferred Certifications * AWS Certified Data Analytics - Specialty * AWS Certified Solutions Architect - Associate * Microsoft Azure Data Engineer Associate * Databricks Certified Data Engineer * Snowflake SnowPro Certification * Certified Data Management Professional (CDMP) Preferred Qualifications * Experience supporting Federal data platforms, reporting systems, or enterprise analytics programs. * Experience supporting large-scale data migration and modernization initiatives. * Experience implementing streaming data pipelines and event-driven architectures. * Experience working with sensitive, regulated, or high-volume datasets. * Familiarity with Federal data governance, security, and compliance requirements. * Experience supporting Artificial Intelligence (AI), Machine Learning (ML), or advanced analytics initiatives. ## Description WINTrio LLC is seeking an experienced Data Engineer to design, develop, and maintain enterprise data platforms supporting Federal analytics, reporting, artificial intelligence, and mission-critical applications. This role is responsible for building scalable ETL/ELT pipelines, integrating structured and unstructured data sources, modernizing legacy data platforms, and enabling secure, reliable, and high-performance data processing across cloud and hybrid environments. The successful candidate will collaborate with data scientists, analysts, application developers, cloud engineers, and business stakeholders to deliver trusted, high-quality data solutions supporting Federal mission objectives. The ideal candidate will possess strong experience in modern data engineering, cloud-native data services, distributed processing, data integration, and enterprise data architecture. Job Responsibilities * Design, develop, and maintain scalable ETL/ELT pipelines supporting batch, streaming, and real-time data processing. * Build enterprise data pipelines using cloud-native services and distributed processing frameworks. * Integrate structured and unstructured data from databases, APIs, files, enterprise applications, streaming platforms, and external systems. * Design and implement logical and physical data models, schemas, and storage architectures supporting analytics and reporting. * Support migration and modernization of legacy data platforms to AWS, Microsoft Azure, or hybrid cloud environments. * Optimize data pipelines for performance, scalability, reliability, fault tolerance, and cost efficiency. * Implement data quality validation, monitoring, reconciliation, and automated pipeline health checks. * Collaborate with data scientists, business analysts, software developers, and application teams to support downstream analytics and operational reporting. * Implement secure data access controls, encryption, governance policies, and compliance requirements supporting Federal data environments. * Support metadata management, data lineage, data catalog integration, and enterprise data governance initiatives. * Develop technical documentation, data flow diagrams, and operational procedures supporting enterprise data platforms. * Contribute to continuous improvement initiatives focused on automation, modernization, and data platform optimization. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [MySQL Protocol Features You Should Be Aware Of](https://www.wearedevelopers.com/videos/100267-mysql-protocol-features-you-should-be-aware-of) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Branch your database like your code: How schema changes and pull requests go hand in hand](https://www.wearedevelopers.com/videos/350-branch-your-database-like-your-code-how-schema-changes-and-pull-requests-go-hand-in-hand) - [Coding for Good: Achieving social change with an app](https://www.wearedevelopers.com/videos/1645-coding-for-good-achieving-social-change-with-an-app) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries)