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Data Engineer

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Work setup
Remote stated — work setup source
This is a remote position. About KIS
Read the full posting
Employment
Unconfirmed
Apply at Kissolutions

What you’ll work on

Full posting
  • You will work closely with engineers, analysts, and stakeholders to ensure high-quality, accessible, and well-structured data across the organization.

  • 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.

From the employer’s posting
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:
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.
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.

What you’ll bring

All qualifications

Core experience

  • Strong experience with SQL, including query optimization, indexing, partitioning, and understanding performance trade-offs.
  • Experience designing and implementing data models for analytics and reporting use cases.
  • Experience building and operating data pipelines using cloud-based data platforms.
  • 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.

Preferred experience

  • Hands-on experience with GCP and BigQuery (desirable)
Qualification wording
Strong experience with SQL, including query optimization, indexing, partitioning, and understanding performance trade-offs.
Experience designing and implementing data models for analytics and reporting use cases.
Experience building and operating data pipelines using cloud-based data platforms.
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.
Hands-on experience with GCP and BigQuery (desirable)

Tools in this posting

  • Python
  • SQL
  • BigQuery
  • Google Cloud (GCP)
Source — Tool mentions in context
- 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.
- 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.
- 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.
- 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.
- Team-oriented mindset with strong communication, collaboration, and problem-solving skills. - Hands-on experience with GCP and BigQuery (desirable)

About Kissolutions

KIS is a global technology consultancy, 100% remote and headquartered in the United States.

In the employer’s words · Read in context

Job description

View original posting ↗

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.
  • Build AI Agents to streamline data platforms, engineering processes and reporting.
  • 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.
  • Previous hands on experience building AI agents.
  • 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.
  • Hands-on experience with GCP and BigQuery (desirable)


  • Your next step

    • Have your CV and examples of relevant work ready.
    • Check the listed location, eligibility and core experience before starting.
    • Ask the employer about the salary range before committing time to the process.

    Complete your application on kissolutions.zohorecruit.com. The employer’s form will show what is required.

    Already applied? Track this application

    Source & posting history

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    Pay

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    Location & working pattern

    Location not supplied.

    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.
    Work authorization

    No clear work-authorization passage found. Eligibility is unconfirmed.

    Status in our records
    Active
    First seen by us
    Aug 22, 2026
    Recorded sightings
    18
    Last seen by us
    Oct 1, 2026

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