Senior Data Engineer, working in AWS
Job Description
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're looking for a Senior Data Engineer to join our Data Infrastructure team — someone who doesn't just build pipelines, but shapes the foundation that every data-dependent team in the company relies on. This is a high-impact, high-autonomy role for an engineer who has seen what great data infrastructure looks like at scale and wants to build it.
You will be a technical anchor for a strategic cloud migration from GCP to AWS, while simultaneously designing and building net-new pipelines and owning the reliability of what already exists. This isn't a role where you'll be handed a ticket queue. You'll help set the technical direction, make architecture decisions, and define the patterns that others will follow.
What You'll Do
GCP → AWS Migration
- Own the technical strategy and execution of migrating large-scale data workloads from GCP to AWS, ensuring continuity, data integrity, and minimal disruption.
- Design migration playbooks and serve as the go-to expert for decisions across compute, storage, and orchestration layers during the transition.
Build Core Infrastructure from the Ground Up
- Architect and implement scalable batch and streaming data pipelines using Apache Spark, Delta Lake, and the medallion architecture.
- Establish standards for pipeline design, data quality, and observability that the broader engineering organization can build on.
Own and Evolve Existing Pipelines
- Take accountability for the reliability, performance, and cost-efficiency of production ETL jobs running on AWS (EMR, Glue) against terabyte-scale datasets.
- Proactively identify and address bottlenecks, technical debt, and opportunities to improve throughput and resilience.
What We're Looking For
Must-Haves
- Strong, hands-on Scala expertise with solid Python proficiency — you're comfortable switching between both and know when each is the right tool.
- Deep experience with Apache Spark for both streaming and batch data processing at scale.
- Proven track record running production ETL workloads on AWS (EMR, Glue) against terabytes of data.
- Experience designing and operating data architectures using Delta Lake and the medallion (Bronze / Silver / Gold) pattern.
- 8+ years of data engineering experience, with a track record of owning critical infrastructure end-to-end.
Nice-to-Haves
- Familiarity with GCP data services and/or hands-on experience migrating data workloads from GCP to AWS.
- Experience with frameworks like Apache Flink, Apache Beam, Airflow, or Databricks.
Who You Are
Beyond the technical checklist, we're looking for someone who:
- Operates with a high degree of ownership — you think about the system holistically, not just your slice of it.
- Communicates clearly with both engineers and non-technical stakeholders, and can translate infrastructure complexity into understandable trade-offs.
- Has strong technical intuition and can navigate ambiguity — at this level, the right path isn't always obvious, and you'll need to define it.
- Has a point of view on data architecture and isn't afraid to advocate for it — while remaining genuinely open to other perspectives.
- Cares about the craft: well-documented, testable, observable pipelines that your teammates can understand and extend.
Why This Role
This is a rare opportunity to build core infrastructure at a meaningful moment in a company's data journey. You'll have the rare combination of greenfield work (building things the right way from scratch), meaningful migration challenges (GCP → AWS at scale), and real ownership of existing production systems.
If you're at the stage of your career where you want your architectural decisions to matter — where the patterns you put in place will influence how data flows across the entire organization for years to come — this is the role for you.
Must-haves:
- Must have strong Scala background and knowledge of Python
- Must have hands on experience handling streaming and batch data with Apache Spark
- Must have experience running ETL jobs on AWS services like EMR or Glue, working with terabytes of data
- Must have experience leveraging Delta lake, medallion architecture for data
Nice-to-haves:
- Knowledge of GCP is a plus
- Migrating data from GCP to AWS is a plus
- experience with frameworks like Flink, Beam, Airflow or Databricks is plus
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
