Data Engineer – ETL, Data Pipelines & Big Data

Position Title: Data Engineer – ETL, Data Pipelines & Big Data 
Location: Remote (U.S.) with Occasional Travel 
Client: Federal / Public Sector Programs 
Work Authorization: Candidates must be authorized to work in the United States. U.S. Citizenship may be required based on client assignment. 
Application Email: careers@wintrio.com 

📩 To apply, please submit your resume to careers@wintrio.com or complete the application form below. 

Job Summary 

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. 

Required Qualifications 

• 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. 

Work Environment 

• Full-time position. 

• Remote within the United States. 

• Standard business hours Monday through Friday. 

• Occasional travel may be required in support of customer meetings, technical workshops, and program activities. 

WINTrio Benefits 

• Healthcare (Medical, Dental, and Vision) 

• Flexible Spending Account (FSA) and Health Savings Account (HSA) 

• 401(k) and Retirement Savings Plan 

• Annual Bonus and Profit Sharing Opportunities 

• Paid Time Off (PTO) and Vacation 

• Employee Assistance Program (EAP) 

• Life, Personal, and Voluntary Disability Insurance 

Growth Opportunities 

There is ample opportunity to grow in multiple dimensions, including data engineering, cloud analytics, artificial intelligence (AI), machine learning (ML), big data platforms, enterprise data modernization, cloud architecture, and business development. We are a completely employee-driven company, and our continued success is built on the talent, dedication, and innovation of our team members. 

Equal Opportunity Employer 

WINTrio LLC is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, age, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.