Remote Data Engineer- Mid Level

We are seeking a highly skilled Data Engineer to design, build, and support scalable data solutions that power critical business reporting, analytics, and operational workloads. This individual will be responsible for developing robust data pipelines, optimizing data platforms, ensuring data quality, and collaborating across engineering and business teams to deliver reliable, high-quality data products., Design, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, and deliver data across the organization.

Build and optimize complex SQL queries, stored procedures, and data workflows for performance and reliability.

Develop Python-based solutions for data processing, automation, and pipeline orchestration.

Design and maintain data models, including dimensional models, normalized schemas, and analytical data structures.

Support and enhance enterprise data warehouse environments, including Snowflake, Teradata, PostgreSQL, Redshift, or BigQuery.

Implement data quality monitoring, validation frameworks, and operational controls to ensure data accuracy and integrity.

Monitor and troubleshoot production data pipelines, ensuring fault tolerance, observability, and operational excellence.

Partner closely with Data Engineering, Infrastructure, Product, Analytics, and Business teams to understand requirements and deliver scalable solutions.

Support cloud-based data infrastructure and data movement across platforms and services.

Contribute to data governance, security, compliance, and best practices across the data ecosystem.

Participate in production support, root cause analysis, and continuous improvement initiatives.

Strong proficiency or 5-7 years in SQL, including advanced querying, joins, optimization, and performance tuning.

-Strong proficiency in Python for data processing, automation, and pipeline development.

-Deep understanding of data modeling, including dimensional modeling, normalization, and schema design.

-Hands-on experience designing and managing ETL/ELT pipelines using Airflow, dbt, or similar orchestration tools.

-Experience with enterprise data warehousing platforms such as Snowflake, Teradata, Redshift, BigQuery, or PostgreSQL.

-Experience working with cloud platforms such as Azure or Google Cloud Platform (GCP).

-Familiarity with cloud storage and compute services.

-Experience with batch and streaming data processing technologies such as Kafka.

-Working knowledge of containerization and deployment technologies, including Docker and Kubernetes.

-Experience supporting cloud-first data platforms and large-scale data environments.

-Strong debugging, troubleshooting, and problem-solving skills.

-Excellent communication skills with the ability to translate technical concepts for non-technical stakeholders. -Experience owning and supporting production-grade data pipelines in a high-availability environment.

-Experience implementing data quality, monitoring, and observability frameworks.

-Understanding of data governance, security, privacy, and compliance requirements.

-Experience collaborating across multiple engineering teams and business stakeholders.

-Demonstrated ownership mindset with a focus on reliability, operational excellence, and continuous improvement.

Drive performance tuning and optimization of large-scale datasets and data processing workloads.

This person is expected to be paid $50-$55hr