Remote Data Engineer: Cloud Pipelines & Warehouses

7Seventy

Northern (KY)

Hybrid

USD 90,000 - 130,000

Full time

34 hours ago

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Job summary

7Seventy is seeking a Data Engineer to join a growing team focused on scalable data infrastructure for client projects. You will design and maintain pipelines, architect cloud data warehouses, and support analytics layers that drive decision-making.

The role blends hands-on execution with strategic thinking, requiring adaptability across tools and environments, and clear communication with technical and non-technical stakeholders. Remote work within the United States is supported.

Qualifications

Bachelor's degree in CS, Engineering, Mathematics, or related field.
2–5 years of data engineering or software engineering experience.
Advanced SQL skills with complex queries and stored procedures.
Strong Python for pipeline scripting, automation, and data processing.
Experience with dbt required; Spark a plus.
Experience with ingestion tools (Fivetran, Airbyte, Rivery, Microsoft Fabric Data Factory).
Experience with orchestration tools (Airflow, Prefect, Azure Data Factory, Microsoft Fabric).
Experience with cloud platforms, Azure preferred, plus AWS or GCP.
Experience with data warehouses (Snowflake, BigQuery, Redshift, Azure Synapse).
Proficient with Git and code-review workflows.
Strong communication and ability to explain technical concepts to non-technical stakeholders.

Responsibilities

Design, build, and maintain scalable data pipelines for clients across industries.
Architect and optimize cloud data warehouse solutions based on client stacks.
Lead data integration projects from source systems through analytics layer.
Work across modern data tools and platforms as client needs evolve.
Collaborate with analysts and data scientists to ensure clean, reliable data.
Champion data quality, testing, and observability across engagements.
Produce technical documentation: pipeline architecture, data dictionaries, lineage, runbooks.
Document engineering decisions and workflows for knowledge transfer.
Research and evaluate emerging technologies; recommend tool investments.
Train and mentor junior team members on engineering standards.
Participate in client-facing requirements gathering and status updates.
Provide support beyond core engineering, including Power BI dashboards and ad hoc reporting.