Staff Software Engineer- Data Ingestion

Jobgether; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Jobgether is seeking a Staff Software Engineer- Data Ingestion in the United States. You will lead the evolution of scalable backend architecture focused on ingestion, storage, and processing, modernizing pipelines and designing distributed systems for growth and high workloads.

You will mentor engineers, influence architecture decisions, and contribute to long‑term technical strategy while delivering reliable software across teams.

Qualifications

• 8+ years of production software engineering experience building scalable systems.
• 4+ years as a technical decision-maker within engineering teams.
• Experience with SQL and large multi-table datasets.
• Architecting, developing, and deploying distributed systems.
• Cloud platform experience (AWS/Azure/GCP).
• Strong CI/CD and data pipelines experience.

Responsibilities

• Identify, architect, and develop scalable data ingestion solutions.
• Lead refactoring and optimization of data pipelines for reliability and performance.
• Design distributed data storage and processing systems for real-time and batch workloads.
• Build ETL/ELT architectures for complex, high-volume data.
• Develop interfaces and abstractions for data infrastructure access.
• Collaborate cross-functionally to shape strategy and execution.
• Establish engineering standards and best practices.
• Evaluate database architectures and performance strategies.
• Design and maintain CI/CD pipelines.
• Monitor performance and optimize system resilience.
• Mentor engineers and promote secure, governed data handling.

Skills

Java

Python

Scala

C#

C++

Go

SQL

Spark

Databricks

Education

Bachelor’s degree or higher in Computer Science or related field

Tools

Docker

Kubernetes

Snowflake

Redshift

AWS/Azure/GCP

CI/CD

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 Staff Software Engineer- Data Ingestion based in United States.

This role will lead the evolution of a highly scalable backend architecture with a strong focus on data ingestion, storage, and processing.

You will modernize existing data pipelines while designing distributed systems capable of supporting significant growth and demanding workloads.

The position combines deep software engineering with architectural leadership, performance optimization, and long-term technical strategy.

You will build clean, expressive interfaces that make complex data infrastructure accessible to applications, analytics platforms, and AI systems.

As a senior technical contributor, you will influence engineering standards, architecture decisions, and product execution across disciplines.

You will also mentor engineers and help establish practices that consistently deliver reliable, high-quality software.

This is an opportunity to shape foundational infrastructure that powers high-performance data experiences at scale.

Accountabilities

• Identify, architect, and develop scalable, highly performant solutions for large-scale data ingestion, storage, and processing.
• Lead the refactoring and optimization of existing data pipelines to improve reliability, scalability, maintainability, and query performance.
• Design and develop next-generation distributed data storage and processing systems capable of supporting large-scale, real-time, and batch workloads.
• Build robust ETL/ELT and data ingestion architectures that efficiently process complex and high-volume datasets.
• Develop clean, expressive interfaces and abstractions that simplify access to complex data infrastructure for web applications, analytics, and AI use cases.
• Work cross-functionally with Product, Engineering, Analytics, and other disciplines to shape product strategy, technical direction, and execution.
• Establish strong foundations for code architecture, engineering quality, reliability, scalability, and maintainability.
• Set and uphold engineering processes, standards, and best practices that support consistent delivery of high-quality software.
• Evaluate database architecture and performance strategies, including partitioning, indexing, replication, sharding, caching, and query optimization.
• Contribute to architecture reviews and make technical decisions that balance immediate business needs with long-term scalability and maintainability.
• Design and maintain CI/CD pipelines and engineering workflows that support reliable, automated software delivery.
• Monitor infrastructure performance, identify bottlenecks, and implement improvements that increase system efficiency and resilience.
• Mentor and coach engineers, provide technical guidance, and help develop engineering capabilities across the organization.
• Promote secure, governed, compliant, and reliable approaches to handling enterprise data and distributed infrastructure.

Requirements

• Bachelor’s or higher degree in Computer Science, Engineering, or a related technical field.
• 8+ years of production-level software engineering experience building highly scalable and reliable systems.
• 4+ years serving as a trusted technical decision-maker within engineering teams, balancing short-term execution with long-term business and technical value.
• 4+ years of experience working with SQL or other database query languages across large, multi-table datasets.
• Demonstrated experience architecting, developing, and deploying large-scale distributed systems.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Strong experience building and maintaining continuous integration and continuous delivery pipelines.
• Strong familiarity with server-side technologies and programming languages such as Java, Python, Scala, C#, C++, or Go.
• Extensive experience designing, optimizing, and orchestrating robust data pipelines and ingestion systems for large-scale real-time and batch processing.
• Experience with data warehouses such as Snowflake or Redshift and analytics technologies such as Spark, SQL, Python, or Databricks.
• Hands‑on experience with containerization technologies including Docker and Kubernetes.
• Strong understanding of distributed architectures, including event‑driven systems and in‑memory computing.
• Deep knowledge of modern database systems and high-performance query optimization techniques, including replication, sharding, partitioning, indexing, and caching.
• Understanding of data security, governance, and compliance principles.
• Experience with infrastructure monitoring, performance optimization, and participation in architecture reviews.
• Strong technical communication, problem-solving, collaboration, and mentoring skills.
• Ability to operate independently on complex technical challenges while influencing engineering direction across teams.

Benefits

• Opportunity to lead the architecture and evolution of large-scale data ingestion and distributed systems.
• High-impact technical role with significant influence over engineering standards and infrastructure strategy.
• Opportunity to mentor engineers and shape technical practices across the organization.
• Exposure to modern cloud, data engineering, distributed systems, and AI-focused infrastructure.
• Work involving scalable real-time and batch data processing and high-performance query optimization.
• Benefits and compensation details are not specified in the provided job description and may be discussed during the hiring process.
• Role requires prolonged periods of sitting and extensive computer and keyboard use, with occasional walking and lifting as needed.