Software Gigs

Own and deliver small to medium machine learning system components from design through production deployment, including building data pipelines, training and evaluating models, and implementing MLOps monitoring. Write high-quality Python code to translate technical requirements into maintainable solutions, working with frameworks like scikit-learn, TensorFlow, PyTorch, and HuggingFace. Design and deploy ML models as microservices, APIs, batch jobs, or streaming components on AWS, with responsibility for model performance metrics, data drift detection, and retraining triggers. Collaborate across Data Engineers, Software Engineers, Data Scientists, and product stakeholders to deliver project objectives.

The Data Architect is a hands-on technical leader responsible for designing and modernizing enterprise data architecture across on-premises and cloud platforms. The role defines scalable data models, integration patterns, and architectural standards for the Data Lake, Data Warehouse, ODS, and cloud platforms while ensuring security, resilience, and high performance. Working closely with engineering, analytics, and business teams, the architect provides technical guidance on modern data systems, governance frameworks, and ETL/ELT pipelines. The position combines strategic vision with practical experience optimizing structured, semi-structured, and unstructured workloads across SQL, NoSQL, and cloud-native systems.

The Data Architect is a hands-on technical leader responsible for designing and modernizing enterprise data architecture across on-premises and cloud platforms. The role defines scalable data models, cloud-native integration patterns, and architectural standards supporting analytics, reporting, and digital banking applications. This position combines strategic architectural vision with practical expertise in designing, implementing, and optimizing modern data systems across structured, semi-structured, and unstructured workloads. The architect provides technical leadership to Data Engineers and cross-functional teams while ensuring secure, resilient, and high-performing data environments.

Lead day-to-day technical project delivery for Distribution Operations initiatives including outage management, solar/battery data integrations, forecasting, automation, and analytics. Transform technical requirements into delivery plans, sprint backlogs, and release milestones while coordinating work across data engineers, architects, cybersecurity teams, and vendors. Manage project controls, scheduling, defect tracking, and comprehensive documentation across integrations, ETL/ELT pipelines, cloud analytics, and Power Platform solutions. Facilitate design reviews, support operational readiness, and ensure technical solutions meet engineering rigor and real-world operational needs.

Design, build, and scale ETL/ELT pipelines and cloud data warehouse infrastructure using Python, SQL, and modern orchestration tools like Apache Airflow or Prefect. Own the end-to-end data infrastructure that powers business intelligence and operational reporting, including data quality checks, anomaly detection, and performance optimization. Collaborate with analytics and software engineering teams to define data modeling standards and maintain infrastructure-as-code deployments using Terraform and CI/CD. Requires 3–6 years of data engineering or backend development experience with advanced SQL, Python, and hands-on work with cloud data warehouses like Snowflake or BigQuery.

Data Engineer II will maintain and enhance data infrastructure, pipelines, and models supporting manufacturing analytics and operational reporting at Dexcom. The role involves writing and optimizing SQL queries, supporting ETL/ELT pipeline development in BigQuery using tools like Google Cloud Dataflow, Apache Beam, and dbt, and troubleshooting data quality issues. You will partner with business stakeholders to gather requirements, document data lineage and workflows, and develop foundational GCP cloud engineering skills. The ideal candidate has a technical degree or equivalent experience and enjoys solving practical operational problems while learning modern cloud data practices.