Data Engineer

We’re looking for an experienced Data Engineer to design, build, and maintain scalable data platforms and pipelines that power analytics, reporting, machine learning, and AI applications.

This is a hands-on engineering role for someone who enjoys solving complex data problems, working with large datasets, and building reliable systems that make data accessible and useful across the organization.

What You’ll Do

• Design, build, and maintain scalable ETL/ELT data pipelines
• Develop data ingestion and transformation processes across structured, semi-structured, and unstructured data sources
• Build and optimize data warehouses, data lakes, and lakehouse architectures
• Develop reliable batch and real-time/streaming data pipelines
• Design data models that support analytics, reporting, operational applications, and AI/ML use cases
• Integrate data from APIs, databases, SaaS platforms, files, and third-party systems
• Improve data quality, reliability, observability, and performance
• Build automated processes for data validation, testing, monitoring, and error handling
• Optimize queries, storage, compute, and pipeline performance
• Implement appropriate data security, governance, access controls, and privacy standards
• Partner with data scientists, AI/ML engineers, analysts, software engineers, and business stakeholders
• Support data infrastructure through CI/CD, infrastructure automation, and modern DataOps practices
• Troubleshoot complex production data issues and identify opportunities to improve platform scalability and reliability

• 4+ years of professional Data Engineering or related experience
• Strong proficiency with SQL
• Strong programming skills in Python
• Experience designing and building production-grade ETL/ELT pipelines
• Experience with modern cloud data platforms such as Snowflake, Databricks, BigQuery, Redshift, or Microsoft Fabric
• Hands-on experience with AWS, Azure, or GCP
• Experience with data transformation and orchestration technologies such as dbt, Airflow, Dagster, Prefect, or similar
• Experience working with relational and NoSQL databases
• Understanding of dimensional modeling, data warehousing, lakehouse architectures, and distributed data processing
• Experience with technologies such as Spark, Kafka, or similar distributed/streaming platforms
• Familiarity with Git, CI/CD, Docker, and modern software engineering practices
• Strong understanding of data quality, lineage, governance, security, and observability
• Ability to translate business and technical requirements into scalable data solutions

Nice to Have

• Experience building data infrastructure for AI/ML and Generative AI applications
• Experience with vector databases, embeddings, or unstructured data pipelines
• Experience with real-time event-driven architectures
• Experience with Terraform or other Infrastructure-as-Code tools
• Experience with Kubernetes
• Experience implementing data catalogs, lineage, and governance platforms
• Experience supporting high-volume or highly distributed data environments