Data Engineer – $56.73 – $71.15 per hour

7Seventy Recruiting; United States; On-site; USD 110,000 - 165,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

401(k)

HSA/FSA

Disability Insurance

Mental Health Benefits

Fitness Reimbursement

Employee Discount

Flexible PTO

Group Life Insurance

EAP AllOne Health

Job summary

7Seventy Recruiting is seeking a Data Engineer to design, build, and scale data systems that support analytics, experimentation, ML, and business decision-making across the organization.

This highly technical role focuses on modern data platform development: architect reliable pipelines, create analytics-ready data products, and collaborate with analytics, product, engineering, and business teams to ensure data is trustworthy, discoverable, and scalable.

Qualifications

• 3 to 5 years of experience in data engineering or software engineering with a data platform focus.
• Proven experience building and scaling modern data platforms and delivering high-impact data solutions.
• Strong communication skills and the ability to collaborate with both technical and non-technical stakeholders.
• Strong interest in building reliable, accessible, and high-quality data products.

Responsibilities

• Design, build, and maintain scalable batch and real-time data pipelines that support analytics, experimentation, and machine learning.
• Contribute to the architecture and ongoing maintenance of the data platform, with a focus on performance, scalability, and cost efficiency.
• Partner with analytics, product, engineering, and business teams to deliver high-quality data solutions that support measurable business outcomes.
• Develop and maintain curated, well-modeled datasets that serve as trusted sources of truth across the organization.
• Promote strong data quality, reliability, and observability practices through testing, monitoring, lineage, and incident response.
• Contribute to engineering standards, reusable patterns, and data platform best practices.
• Improve infrastructure, developer workflows, CI/CD processes, and data platform tooling.

Skills

Python

SQL

Data engineering

Cloud data platforms

CI/CD

Data quality

Stakeholder collaboration

Tools

Snowflake

BigQuery

Databricks

Airflow

Dagster

Kubernetes

Terraform

Job description

About the Role

This opportunity is for a Data Engineer to design, build, and scale the data systems that support analytics, experimentation, machine learning, and business decision-making across the organization.

This is a highly technical, hands-on role focused on modern data platform development. You will architect reliable pipelines, create analytics-ready data products, and collaborate closely with analytics, product, engineering, and business teams to ensure data is trustworthy, discoverable, scalable, and ready for use.

What You’ll Do

• Design, build, and maintain scalable batch and real-time data pipelines that support analytics, experimentation, and machine learning.
• Contribute to the architecture and ongoing maintenance of the data platform, with a focus on performance, scalability, and cost efficiency.
• Partner with analytics, product, engineering, and business teams to deliver high-quality data solutions that support measurable business outcomes.
• Develop and maintain curated, well-modeled datasets that serve as trusted sources of truth across the organization.
• Promote strong data quality, reliability, and observability practices through testing, monitoring, lineage, and incident response.
• Contribute to engineering standards, reusable patterns, and data platform best practices.
• Improve infrastructure, developer workflows, CI/CD processes, and data platform tooling.

Qualifications

• 3 to 5 years of experience in data engineering or software engineering with a strong focus on data platform development.
• Proven experience building and scaling modern data platforms and delivering high-impact data solutions.
• Strong communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders.
• Strong interest in building reliable, accessible, and high-quality data products.

Technical Expertise

• Strong proficiency in Python and SQL.
• Experience with modern cloud data warehouses and data lakes such as Snowflake, BigQuery, or Databricks.
• Experience building batch pipelines using DAG-based orchestration tools such as Dagster or Airflow.
• Experience with event-driven architectures using technologies such as Kafka, Kinesis, or Event Hubs.
• Experience developing real-time or streaming pipelines using Apache Beam, Flink, or Spark Streaming.
• Experience deploying applications and services to Kubernetes.
• Experience with Kubernetes ecosystem tools such as ArgoCD, Helm, or Istio.
• Experience applying DevOps concepts to data workflows, including CI/CD, observability, monitoring, and lineage.
• Experience with infrastructure-as-code tools such as Terraform.

Benefits

• Medical, dental, and vision insurance.
• 401(k) retirement savings plan.
• HSA or FSA eligibility.
• Long-term and short-term disability insurance.
• Mental health benefits.
• Fitness reimbursement program.
• 25% employee discount and membership benefits.
• Flexible paid time off.
• Group life insurance.
• Employee Assistance Program through AllOne Health.