Data Engineer (Remote)

7Seventy Recruiting; United States; Vor Ort; USD 150.000 - 200.000; Vollzeit

Benefits dieser Stelle

Healthcare coverage

Life insurance

401(k) retirement plan with employer 1

Paid time off

Parental leave (12 weeks)

Disability coverage

Employee Assistance Program

Zusammenfassung

7Seventy Recruiting is seeking a Senior Data Engineer in the United States to modernize our data platform by designing and maintaining reliable data pipelines, models, schemas, and transformations. You will improve data architecture, governance, and build scalable solutions that support analytics and business operations.

You will work hands-on with Snowflake, dbt, SQL, and cloud-based data infrastructure, implementing Medallion architecture, optimizing warehouse performance, and integrating data

Qualifikationen

• 6+ years hands-on data engineering experience with dbt Core/Cloud, Snowflake, Fivetran, Amazon RDS, PostgreSQL.
• Experience designing Medallion data architecture (Bronze/Silver/Gold) in production.
• Production experience with Snowflake deployments and data warehouse performance optimization.
• Experience extracting/integrating data from SaaS platforms (e.g., Salesforce) using ETL tools like Fivetran.
• Production experience with dbt Cloud or similar data transformation management platforms.
• Experience managing operational databases, including backup, recovery, performance tuning, data modeling, and scaling.

Aufgaben

• Design, develop, manage, and maintain data pipelines, data models, schemas, and related artifacts as part of data platform modernization.
• Build scalable data transformations using dbt and modern practices.
• Establish data quality standards, version control, automated testing, and technical documentation.
• Collaborate with cross-functional teams to improve tools, infrastructure, and workflows.
• Translate data requirements from stakeholders into dependable technical data solutions.
• Evaluate new data engineering tools and approaches to improve reliability and scalability.
• Work with CI/CD workflows and IaC tools (GitHub Actions, Terraform) to deploy pipelines.
• Monitor and troubleshoot production data pipelines to ensure quality and availability.
• Develop and update technical documentation for pipelines, models, and workflows.

Kenntnisse

dbt development

Snowflake

SQL

Data modeling

Data pipelines

Airflow

Terraform

GitHub Actions

Python/Java/Scala

Data governance

NoSQL databases

Medallion architecture

SaaS data integration

PostgreSQL

Tools

dbt Core/Cloud

Snowflake deployments

Fivetran

Amazon RDS

PostgreSQL

Dagster

Apache Airflow

Terraform

GitHub Actions

Jobbeschreibung

Experience: 6+ years in data engineering

Core Areas: Data Engineering, Data Pipelines, ETL/ELT, Snowflake, dbt, SQL, Data Modeling, Data Warehouse Optimization

Compensation: $150,000-$200,000 annually

About the Role

This Senior Data Engineer position focuses on modernizing a data platform by designing, developing, and maintaining reliable data pipelines, data models, schemas, and transformations. The role involves improving data architecture, strengthening data quality and governance practices, and building scalable data engineering solutions that support analytics and business operations.

The position requires hands‑on expertise with Snowflake, dbt, SQL, data orchestration, and cloud‑based data infrastructure. Responsibilities include implementing Medallion data architecture, optimizing data warehouse performance, and integrating data from SaaS and operational systems. The engineer will collaborate with data scientists, analysts, software engineers, platform engineers, and business stakeholders to translate data requirements into dependable technical solutions.

What You’ll Do

• Design, develop, manage, and maintain data pipelines, data models, schemas, and related data artifacts as part of ongoing data platform modernization.
• Build and maintain scalable data transformations using dbt and modern data engineering practices.
• Establish and promote engineering standards for data quality, version control, automated testing, and technical documentation.
• Collaborate with data engineers, software engineers, and platform engineers to improve engineering tools, infrastructure, workflows, and development practices.
• Partner with data scientists, analysts, business stakeholders, and cross-functional data teams to gather requirements and translate them into technical data solutions.
• Evaluate emerging data engineering tools, technologies, and approaches to improve the reliability, scalability, and efficiency of the data ecosystem.
• Work with platform engineering teams to integrate and deploy data pipelines through shared CI/CD workflows and Infrastructure as Code tools, including GitHub Actions and Terraform.
• Monitor, troubleshoot, and maintain production data pipelines, identifying and resolving issues affecting data quality, reliability, and availability.
• Develop and update technical documentation covering data pipelines, data models, engineering workflows, and operational procedures.

Qualifications

Required Experience

• 6+ years of hands‑on data engineering experience with technologies such as dbt Core or dbt Cloud, Snowflake, Fivetran, Amazon RDS, and PostgreSQL.
• Practical experience designing and implementing Medallion data architecture, including Bronze, Silver, and Gold data layers, in production environments.
• Production experience operating and managing Snowflake deployments, including data warehouse performance optimization.
• Experience extracting and integrating data from SaaS platforms such as Salesforce using ETL tools including Fivetran.
• Production experience using dbt Cloud or other source‑driven data transformation management platforms.
• Experience managing operational databases, including backup, recovery, performance tuning, data modeling, and scaling.

Required Skills

• Strong proficiency in dbt development, including established coding conventions, modular data transformations, and development best practices.
• Extensive knowledge of SQL and NoSQL data stores, relational databases, and data modeling techniques.
• Experience with data pipeline orchestration platforms such as Apache Airflow, Dagster, or comparable technologies.
• Ability to implement automated data quality checks, dbt tests, and data validation frameworks.
• Experience with CI/CD pipelines, Git‑based version control, and automated deployment processes supporting data engineering workflows.
• Demonstrated ability to optimize Snowflake performance, dbt models, SQL queries, and data warehouse operating costs.
• Knowledge of Infrastructure as Code and Database Change Management tools and processes.
• Programming experience with Python, Java, Scala, or similar languages.
• Strong troubleshooting, analytical problem‑solving, and technical documentation capabilities.
• Self‑motivation, focus, and commitment to delivering value through reliable engineering solutions.
• Effective communication, collaboration, and knowledge‑sharing skills, with the ability to work across multidisciplinary engineering and business teams.

Preferred Qualifications

• Experience preparing and structuring data for analysis using Tableau or other business intelligence platforms.
• Familiarity with Sigma Computing.
• Experience using Fivetran Activations.
• Experience working in financial services environments.
• Familiarity with SOC 2 and PCI DSS compliance requirements.
• Healthcare coverage and life insurance.
• 401(k) retirement plan with employer matching.
• Paid time off.
• 12 weeks of paid parental leave.
• Short‑term and long‑term disability coverage.
• Employee Assistance Program.
• Spending accounts for transit, parking, medical expenses, and dependent care.
• Insurance discounts for home, auto, and pet coverage.