Senior Data Engineer

Far Coder; Northern (KY); Hybrid; USD 140,000 - 190,000; Full time

Job summary

Kunai is hiring a remote Senior Data Engineer in the United States to join a full-time data engineering program supporting modernization of financial services. You will build and optimize data pipelines to enable real-time insights and scalable analytics.

You will design DynamoDB data models, implement ETL/ELT processes, and collaborate with scientists and engineers while mentoring junior team members. Spark experience is a strong plus but not required.

Qualifications

• 5+ years of professional experience in data engineering or software engineering focused on data-centric solutions.
• Expert Python programming skills with data processing and pipeline development.
• Deep experience with AWS DynamoDB, including data modeling and performance tuning.
• Cloud computing fundamentals with AWS.
• Strong experience building high-scale ETL/ELT pipelines and batch/streaming data.
• Experience with distributed data processing (Apache Spark a plus).
• NoSQL data storage experience with DynamoDB or similar.
• Ability to collaborate across product, data science, and operations.

Responsibilities

• Data Pipeline Development & Optimization Design, build, and maintain scalable, reliable, high-performance data pipelines using Python and AWS DynamoDB.
• Implement robust ETL/ELT processes for both batch and streaming data workloads.
• Collaborate with data scientists, analysts, and backend engineers to ensure data accessibility and integrity.
• Data Architecture & Storage Develop and optimize DynamoDB data models and indexing strategies for high throughput.
• Leverage cloud-native data storage and serverless architectures for cost-efficient, scalable systems.
• Big Data & Analytics Contribute to Spark-based analytics for large-scale data transformations where applicable.
• Monitor and optimize pipeline performance, scalability, and latency.
• Data Quality & Governance Establish data validation, monitoring, and alerting mechanisms.
• Collaborate on data governance, compliance, and security best practices.
• Mentor junior team members and promote knowledge sharing across the engineering organization.

Skills

Python

AWS

DynamoDB

Kubernetes

Terraform

CI/CD

Spark

Education

Bachelor's Degree

Job description

Kunai is hiring a remote candidate for Senior Data Engineer. This is a full time position. Work location: USA. The role typically involves technologies such as Kubernetes, Terraform, CI/CD, Python, AWS, Docker. Kunai builds full-stack technology solutions for banks, credit and payment networks, infrastructure providers, and their customers. Together, we are changing the world’s relationship with financial services. At Kunai, we help our clients modernize, capitalize on emerging trends, and evolve their business for the coming decades by remaining tech-agnostic and human-centered. We are seeking a Senior Data Engineer with deep Python and DynamoDB expertise to join a high-impact data engineering program supporting the modernization and scaling of financial services platforms. In this hands-on role, you will build and optimize data pipelines and systems that ingest, process, and analyze vast volumes of transactional and operational data, enabling real-time insights and driving data-driven decision-making at scale. Experience with Spark is a strong plus but not required.

WHAT YOU'LL DO

• Data Pipeline Development & Optimization Design, build, and maintain scalable, reliable, and high-performance data pipelines using Python and AWS DynamoDB.
• Implement robust ETL/ELT processes for both batch and streaming data workloads.
• Collaborate with data scientists, analysts, and backend engineers to ensure data accessibility and integrity.
• Data Architecture & Storage Develop and optimize DynamoDB data models and indexing strategies to meet diverse access patterns and high throughput requirements.
• Leverage cloud-native data storage solutions and serverless architecture to drive cost-efficient and scalable systems.
• Big Data & Analytics Contribute to the implementation and tuning of distributed data processing frameworks such as Apache Spark to support large-scale data transformations and analytics, where applicable.
• Monitor and optimize pipeline performance, scalability, and latency.
• Data Quality & Governance Establish data validation, monitoring, and alerting mechanisms to ensure pipeline reliability and accuracy.
• Collaborate with stakeholders on data governance, compliance, and security best practices.
• Technology Growth & Collaboration Participate in architectural discussions and code reviews, advocating for best practices in Python development and cloud data engineering.
• Mentor junior team members and promote knowledge sharing across the engineering organization.

REQUIRED SKILLS & EXPERIENCE

• Core Engineering 5+ years of professional experience in data engineering or software engineering roles focused on data-centric solutions.
• Expert Python programming skills with a strong focus on data processing and pipeline development.
• Deep experience designing and implementing solutions with AWS DynamoDB, including data modeling, performance tuning, and capacity planning.
• Thorough understanding of cloud computing fundamentals (AWS preferred).
• Data Engineering & Processing Solid experience building high-scale ETL/ELT pipelines and working with streaming and batch data.
• Familiarity with distributed data processing frameworks; experience with Apache Spark is a significant plus but not required.
• Data Storage Systems Experience working with NoSQL databases such as DynamoDB, Cassandra, or similar.
• Comfortable with schema design trade-offs and query pattern optimizations in key-value and document stores.
• Collaboration & Communication Track record of collaborating effectively in cross-functional teams involving product, data science, and operations.
• Strong verbal and written communication skills; able to explain technical concepts clearly to non-technical stakeholders.
• Ability to thrive in fast-paced, evolving environments with changing requirements.

NICE TO HAVE

• Hands-on experience with Apache Spark or other big data processing frameworks.
• Familiarity with other AWS services such as Lambda, Kinesis, Glue, or Redshift.
• Prior experience working in financial services or payments industry data platforms.
• Exposure to containerized/cloud-native deployments (e.g., Docker, Kubernetes). Experience with CI/CD pipelines and infrastructure-as-code tools such as Terraform or CloudFormation.

At this time, we are unable to provide sponsorship for this role. Our success over the past 20 years is rooted in our exceptional team, which thrives in a culture of collaboration, creativity, and continuous learning. We are proud to offer our employees a range of benefits, including competitive compensation, professional development opportunities, and flexible work arrangements, all designed to help them thrive. As we continue to expand, we remain committed to cultivating an environment where people feel valued, have a voice, and are given the tools to grow - both personally and professionally - while pushing the boundaries of innovation in the fintech industry.

Minimum Degree Required: Bachelor’s Degree, in lieu of a degree, demonstrating in addition to the minimum years of experience required for the role, three years of specialized training and/or progressively responsible work experience in technology for each missing year of college is required.

Skills required for this role include Kubernetes, Terraform, CI/CD, and related tools for day-to-day development. Seniority level: Senior.