Senior Data Engineer

Kpler
Greece
Hybrid

Who this role is best for

Geared toward experienced data engineers comfortable with building scalable data pipelines and cloud-native infrastructure on AWS.

Best fit for

  • Experienced data engineers with a background in cloud infrastructure and distributed systems
    — “Provision and manage cloud-native data infrastructure on AWS using Terraform, Docker, and automated CI/CD practices.”
  • Candidates who have worked with polyglot environments and can translate domain requirements into data products
    — “Collaborate cross-functionally with Product Managers, SRE, Platform Engineers, and Data Scientists to translate complex domain needs into performant data products.”
  • Individuals with a track record of optimizing data pipelines and ensuring data reliability
    — “Ensure end-to-end data quality, freshness, and reliability by implementing automated validation, monitoring frameworks, and strict SLA tracking.”

Things to consider

  • This role demands a high level of experience in production-grade systems and cloud management
    — “6+ years of professional software or data engineering experience building complex, production-grade data processing systems.”
  • The position involves maintaining and evolving data architecture across multiple backend technologies
    — “Maintain and evolve data architecture across polyglot backend microservices (Python/FastAPI, PHP, Java/Scala).”

How to stand out

  • Highlight experience in optimizing cloud resources and pipeline performance in your resume and interviews
    — “Drive operational and cost efficiency across data infrastructure, optimizing cloud resource usage and pipeline performance.”
  • Showcase your ability to work with multiple programming languages in a polyglot environment
    — “Practical experience writing clean, maintainable code in polyglot environments (Python, Java/Scala, or PHP).”
  • Demonstrate your hands-on skills with Apache Spark, Kafka, and Airflow in your technical summaries
    — “Architect, build, and optimize scalable data pipelines and stream-processing workflows using Python, Apache Spark, Kafka, and Airflow.”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • architected scalable data pipelines
  • optimized cloud resource usage
  • collaborated with cross-functional teams
Typical background
data engineeringcloud infrastructuresoftware engineering

Skills & requirements

Required

Data EngineeringCloud InfrastructureData PipelinesDistributed SystemsDatabase DesignCi/cd Practices

Preferred

Restful ApisTime-series DataGeospatial DataMaritime Logistics Data

Stack & domain

PythonApache SparkKafkaAirflowTerraformDockerCI/CDSQLNoSQLFastapiPHPJavaScalaCommoditiesEnergyMaritime

About the role

Original posting from Kpler via Lever

At Kpler, we are dedicated to helping our clients navigate complex markets with ease. By simplifying global trade information and providing valuable insights, we empower organisations to make informed decisions in commodities, energy, and maritime sectors.

Since our founding in 2014, we have focused on delivering top-tier intelligence through user-friendly platforms. Our team of over 850 experts from 69 countries works tirelessly to transform intricate data into actionable strategies, ensuring our clients stay ahead in a dynamic market landscape. Join us to leverage cutting-edge innovation for impactful results and experience unparalleled support on your journey to success.

Key Responsibilities:

-

Architect, build, and optimize scalable data pipelines and stream-processing workflows using Python, Apache Spark, Kafka, and Airflow.

-

Maintain and evolve data architecture across polyglot backend microservices (Python/FastAPI, PHP, Java/Scala) to support continuous analytics delivery.

-

Ensure end-to-end data quality, freshness, and reliability by implementing automated validation, monitoring frameworks, and strict SLA tracking.

-

Provision and manage cloud-native data infrastructure on AWS using Terraform, Docker, and automated CI/CD practices.

-

Collaborate cross-functionally with Product Managers, SRE, Platform Engineers, and Data Scientists to translate complex domain needs into performant data products.

-

Drive operational and cost efficiency across data infrastructure, optimizing cloud resource usage and pipeline performance.

Experience & Background:

What you'll need (Must-haves)

-

6+ years of professional software or data engineering experience building complex, production-grade data processing systems.

-

Strong expertise in Python and hands-on experience with distributed data processing tools such as Apache Spark, Kafka, or Airflow.

-

Advanced knowledge of database design, SQL performance tuning, and data modeling across relational and NoSQL stores.

-

Proven experience managing cloud infrastructure on AWS, utilizing Terraform, Docker, and modern CI/CD pipelines.

-

Practical experience writing clean, maintainable code in polyglot environments (Python, Java/Scala, or PHP).

Nice-to-haves

-

Experience building RESTful APIs using Python frameworks like FastAPI.

-

Background handling high-throughput time-series, geospatial, or maritime logistics datasets.

-

Exposure to cloud FinOps, observability, and cost management tooling (e.g., Datadog, Astronomer).

We are a dynamic company dedicated to nurturing connections and innovating solutions to tackle market challenges head-on. If you thrive on customer satisfaction and turning ideas into reality, then you’ve found your ideal destination. Are you ready to embark on this exciting journey with us?

We make things happen

We act decisively and with purpose, going the extra mile.

We build
together

We foster relationships and develop creative solutions to address market challenges.

We are here to help

We are accessible and supportive to colleagues and clients with a friendly approach.

Our People Pledge

Don’t meet every single requirement? Research shows that women and people of color are less likely than others to apply if they feel like they don’t match 100% of the job requirements. Don’t let the confidence gap stand in your way, we’d love to hear from you! We understand that experience comes in many different forms and are dedicated to adding new perspectives to the team.

Kpler is committed to providing a fair, inclusive and diverse work-environment. We believe that different perspectives lead to better ideas, and better ideas allow us to better understand the needs and interests of our diverse, global community. We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer.

By applying, I confirm that I have read and accept the Staff Privacy Notice

Source: Kpler careers (Lever)

Similar roles

More roles at Kpler