This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer based in the United States.
This role plays a key part in shaping and scaling modern enterprise data platforms that power analytics, reporting, and data-driven decision-making across the organization. You will design and build robust batch and streaming data pipelines that transform complex, multi-source datasets into reliable, analytics-ready assets. Working within a cloud-first environment, you will contribute to the evolution of data architecture supporting lakehouse, warehouse, and data lake strategies. The position involves close collaboration with architecture, analytics, governance, and application teams to translate business needs into scalable engineering solutions. You will also ensure data systems are performant, secure, and compliant with regulatory requirements. This is a highly technical, hands-on role suited for someone who enjoys solving complex data challenges while enabling self-service analytics and advanced insights at scale.
Accountabilities:
In this role, you will design, build, and maintain enterprise-grade data pipelines and platforms that enable reliable analytics and business intelligence.
- Develop and maintain scalable batch and streaming data pipelines supporting analytics, reporting, and downstream applications
- Build and optimize data ingestion, transformation, and orchestration workflows across structured and semi-structured data sources
- Design and maintain curated, analytics-ready data models including dimensional, canonical, and domain-oriented datasets
- Implement cloud-based data solutions aligned with enterprise architecture standards and security requirements
- Ensure data reliability through performance tuning, observability, validation rules, and data quality controls
- Support cloud data platform evolution including architecture improvements, tooling decisions, and modernization initiatives
- Collaborate with analytics, data science, and reporting teams to enable self-service data consumption
- Translate business requirements into scalable and reusable data structures and pipelines
- Ensure compliance with governance, privacy, metadata, and data lineage standards
- Promote engineering best practices including CI/CD, version control, testing, and documentation
Requirements:
This role requires strong data engineering expertise, cloud platform experience, and the ability to design scalable, high-performance data systems.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field (Master’s preferred)
- 5+ years of experience in data engineering, analytics engineering, or data platform development
- Strong proficiency in SQL and at least one programming language such as Python, Java, or Scala
- Hands-on experience building data pipelines, data models, and distributed data processing systems
- Strong expertise with AWS services such as Lambda, Glue, Step Functions, S3, EMR, SNS/SQS, Lake Formation, and CloudWatch
- Solid understanding of data architecture patterns including data lakes, lakehouses, and analytical warehouses
- Experience with cloud platforms (AWS, Azure, or GCP) and modern DevOps practices is a plus
- Familiarity with infrastructure-as-code tools (e.g., Terraform, CloudFormation) and CI/CD pipelines
- Strong analytical and problem-solving skills with the ability to handle complex data challenges
- Excellent communication skills to translate technical concepts for both technical and non-technical stakeholders
Benefits:
- Competitive base salary ranging from $130,000 to $150,000 annually
- Comprehensive health, dental, and vision insurance
- Retirement savings plans with employer contributions
- Flexible and hybrid work arrangements depending on role and location
- Professional development and continuous learning opportunities
- Exposure to modern cloud data technologies and enterprise-scale systems
- Collaborative, cross-functional environment supporting innovation and data-driven culture
- Paid time off and holidays
- Commitment to diversity, equity, and inclusive workplace practices