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Data Engineer

KIS Solutions

Role overview

Qualifications

  • Professional experience as a Data Engineer working with production-grade data pipelines.
  • Strong experience with SQL, including query optimization, indexing, partitioning, and understanding performance trade-offs.
  • Professional experience writing Python for data transformations, following good software design and modularization practices.
  • Experience building and operating data pipelines using cloud-based data platforms.

Responsibilities

  • Design, build, and maintain end-to-end data pipelines, including batch and/or streaming workflows.
  • Develop and operate reliable, scalable, and high-performing ETL/ELT workflows.
  • Write efficient, production-grade SQL queries for data extraction, transformation, and analytics use cases.
  • Ensure data quality by implementing automated validation checks.

Key facts

Hard skills

Data Engineering SQL (Programming Language) Python (Programming Language) Data Modeling gRPC BigQuery Data Security Data Governance

Other skills

  • Communication
  • Collaboration
  • Problem Solving
  • Time Management

About the company

KIS Solutions logo

KIS Solutions

IT Services & IT Consulting

Too often corporate IT teams and business counterparts are at odds. This is in large part because technologists too often focus on the technology solution itself rather than the underlying business problem. At KIS solutions we believe that technology is a tool to solve business problems. We focus on the business problem and operational processes which our solutions support. When building technology systems, the most challenging part of the development process is often deciding “what to build” not “how to build it”. It is sadly true however that many corporate IT teams spend so much their time focusing on the “how” rather than the “what”. Once you have answered the challenging questions around “what to build”, the rest falls into place. Building the system should be simple! Founder Benjamin Quintana is an IT professional and entrepreneur with nearly 20 years of experience delivering impactful solutions across a broad range of industries. Ben has extensive experience with customer data analytics, data cleansing, customer identification, customer preference management, call center and logistical systems. He also has deep industry expertise in loyalty marketing applications and was directly responsible for the infrastructure of the loyalty program of a leading hotel group.

Company details

IndustryIT Services & IT Consulting
Company size51 - 200

Links

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Job description

This is a remote position.


About KIS

KIS is a global technology consultancy, 100% remote and headquartered in the United States. We partner with companies ranging from innovative startups to large multinational organizations, helping them build modern, scalable, and high-impact technology solutions.

Our global team works on challenging projects across different industries, combining technical excellence, innovation, and close collaboration with our clients.

We are currently looking for a Mid-Level Data Engineer to join our team and work on a challenging project for one of KIS's leading international clients.

What You'll Do

As a Mid-Level Data Engineer, you will be responsible for designing, building, and maintaining reliable and scalable data solutions. You will work closely with engineers, analysts, and stakeholders to ensure high-quality, accessible, and well-structured data across the organization.

Your responsibilities will include:

  • Design, build, and maintain end-to-end data pipelines, including batch and/or streaming workflows, from ingestion through transformation and delivery.
  • Develop and operate reliable, scalable, and high-performing ETL/ELT workflows.
  • Write efficient, production-grade SQL queries for data extraction, transformation, and analytics use cases.
  • Implement and maintain data models, including star schemas and incremental models, optimized for analytics and reporting.
  • Develop reusable, modular, and maintainable Python code for data transformations and pipeline logic.
  • Monitor data pipelines, troubleshoot failures, and perform root cause analysis across code, orchestration tools, data sources, and cloud services.
  • Ensure data quality by implementing automated validation checks, including schema validation, freshness checks, and row-level assertions.
  • Collaborate with analysts, backend engineers, and other stakeholders to define data contracts and ensure reliable data availability.
  • Actively participate in planning, estimation, and prioritization of data engineering tasks.
  • Proactively identify risks related to performance, scalability, and data integrity, proposing effective mitigation strategies.
  • Contribute to the continuous improvement of data platforms, engineering processes, and team best practices.
  • Write and maintain clear technical documentation for data pipelines, schemas, and data lineage.
  • Communicate clearly with team members and clients, proactively raising questions and concerns when requirements or priorities are unclear.


Requirements

  • Professional experience as a Data Engineer working with production-grade data pipelines.
  • Strong experience with SQL, including query optimization, indexing, partitioning, and understanding performance trade-offs.
  • Professional experience writing Python for data transformations, following good software design and modularization practices.
  • Experience designing and implementing data models for analytics and reporting use cases.
  • Experience building and operating data pipelines using cloud-based data platforms.
  • Hands-on experience with GCP and BigQuery.
  • Experience operating data pipelines, including error handling, monitoring, troubleshooting, and data quality processes.
  • Knowledge of fundamental data security and governance practices, including access control, data masking, and PII handling.
  • Ability to deliver less complex tasks independently and handle more complex challenges with appropriate guidance.
  • Strong sense of ownership, responsibility, and accountability for data workflows and deliverables.
  • Good organizational and time management skills, with the ability to estimate effort and meet delivery deadlines.
  • Advanced English level for effective collaboration with global clients and distributed teams.
  • Team-oriented mindset with strong communication, collaboration, and problem-solving skills.


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    MR

    Marcus Rivera

    Chief Revenue Officer

    m.rivera@company.com
    linkedin.com/in/marcusrivera
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