Design and build scalable data lake architecture and cloud-native data platforms. Develop distributed backend systems, APIs, and event-driven services. Collaborate with cross-functional teams to translate business requirements into scalable technical solutions.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr. Software Engineer - Big Data, Data Lake based in the United States.
This is an exciting opportunity for an experienced software engineer to help shape the foundation of a next-generation data platform powering large-scale, data-intensive applications. In this role, you will design and build scalable data ingestion, transformation, and integration solutions using modern cloud-native technologies. Working at the intersection of data engineering and backend development, you will contribute to the architecture of a robust data lake ecosystem that supports APIs, analytics, machine learning initiatives, and customer-facing products. You'll collaborate closely with cross-functional teams while driving technical excellence across distributed systems, event-driven architectures, and high-volume data pipelines. The position offers significant ownership, technical influence, and the flexibility of a fully remote environment.
Accountabilities
- Design, develop, and maintain scalable data lake architecture and cloud-native data platforms that support enterprise applications and analytics initiatives.
- Build and optimize high-volume data ingestion, transformation, and integration pipelines for structured and semi-structured data from multiple internal and external sources.
- Develop distributed backend systems, APIs, and event-driven services using modern programming languages and cloud technologies.
- Architect and implement reliable data workflows leveraging AWS-native services, serverless technologies, and orchestration frameworks.
- Collaborate with product, analytics, business intelligence, and engineering teams to translate business requirements into scalable technical solutions.
- Ensure data quality, integrity, governance, and security through effective monitoring, cleansing, validation, and anomaly detection processes.
- Design and maintain high-availability systems capable of supporting multi-tenant environments and large-scale workloads.
- Participate in on-call rotations, troubleshooting efforts, incident response activities, and operational excellence initiatives.
- Create technical documentation, architecture diagrams, and implementation plans that support long-term platform scalability and maintainability.
- Contribute to continuous improvement initiatives, cloud infrastructure optimization, deployment automation, and engineering best practices.
- 7-10 years of professional software engineering experience, preferably within data-rich applications, big data environments, or SaaS platforms.
- Strong expertise with AWS cloud services, including S3, Glue, Athena, Lake Formation, Lambda, Step Functions, API Gateway, Kinesis, and related technologies.
- Advanced experience designing and implementing large-scale data pipelines, ETL processes, and data lake architectures.
- Expert-level proficiency in Python and SQL for distributed systems, data engineering, and backend development.
- Strong experience building backend services and APIs using TypeScript and Node.js.
- Deep understanding of event-driven architectures, orchestration frameworks, asynchronous processing, and distributed systems design.
- Experience working with cloud data warehouses such as Snowflake, Redshift, BigQuery, Athena, or similar platforms.
- Knowledge of data quality frameworks, entity resolution, data cleansing, anomaly detection, and governance practices.
- Hands-on experience integrating cloud-based data platforms with reporting, analytics, and third-party business systems.
- Familiarity with CI/CD pipelines, infrastructure automation, serverless architectures, containerized services, and deployment best practices.
- Strong understanding of security principles related to data storage, API access, permissions, and cloud infrastructure.
- Excellent communication, documentation, collaboration, and problem-solving skills.
- Proven ability to lead technical initiatives while remaining highly hands-on with implementation and delivery.
- Experience supporting production environments and participating in on-call rotations.
- Exposure to AI-assisted development tools, machine learning workflows, or generative AI technologies is considered a plus.
Interested in remote work opportunities in Data Science? Discover Data Science Remote Jobs featuring exclusive positions from top companies that offer flexible work arrangements.
- Competitive salary ranging from $120,000 to $150,000 annually.
- Fully remote work environment within approved U.S. locations.
- Comprehensive health, dental, and vision coverage for eligible employees.
- 401(k) plan with company matching contributions.
- Internet or mobile phone reimbursement subsidy.
- Generous paid time off program.
- Paid holidays, including additional cultural and heritage celebration days.
- Half-day Summer Fridays.
- Professional development and career growth opportunities.
- High-autonomy environment with meaningful ownership of technical decisions.
- Collaborative and supportive engineering culture focused on innovation and continuous learning.
- Inclusive workplace committed to diversity, equity, and belonging.
Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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