Data Platform Engineer (GCP)

Far Coder; Northern (KY); On-site; USD 60,000 - 110,000; Full time

Job summary

Innodata Inc. is seeking a hands-on Data Platform Engineer (GCP) to support and optimize large-scale production data platforms on Google Cloud. This full-time, USA-based role emphasizes platform reliability, production support, and proactive improvements.

The ideal candidate has extensive GCP experience, strong SQL and Python skills, and is comfortable troubleshooting pipelines and orchestrations with Airflow/Cloud Composer. Collaboration with cross-functional teams is essential.

Qualifications

• 3–7+ years in Data/Cloud or Platform Engineering.
• Strong hands-on experience on Google Cloud Platform (GCP).
• Proficient with BigQuery and Cloud Spanner.
• Experience with Dataflow, Pub/Sub, and Airflow-based pipelines.

Responsibilities

• Support, maintain, and enhance large-scale production GCP data platforms.
• Troubleshoot DAG failures and optimize Airflow workflows for reliability.
• Monitor health, optimize performance, and improve data latency.
• Collaborate with Data Engineering, BI/Analytics, and Infra teams.

Skills

SQL

Terraform

CI/CD

Python

Rust

GCP

Tools

BigQuery

Cloud Spanner

Dataflow

Pub/Sub

Cloud Composer

Apache Airflow

Cloud Storage

IAM

Vertex AI

Job description

Innodata Inc. is hiring a remote candidate for Data Platform Engineer (GCP). This is a full time position. Work location: USA. The role typically involves technologies such as SQL, Terraform, CI/CD, Python, Rust, GCP. Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.

Scope of the Role

We are looking for a hands-on GCP / Data Platform Engineer to support, maintain, and enhance large-scale production data platforms running on Google Cloud. The role is focused on platform reliability, production support, troubleshooting, performance optimization, and continuous enhancement rather than greenfield platform development. The ideal candidate can quickly understand a complex existing environment, diagnose issues across data pipelines and infrastructure, and implement practical improvements with minimal disruption. Experience operating large-scale, business-critical data platforms in complex enterprise environments is preferred.

What You’ll Own

• Support and maintain production GCP data platforms, pipelines, and workflows across batch and streaming workloads.
• Support production workflows orchestrated through Cloud Composer / Apache Airflow, including troubleshooting DAG failures, dependencies, scheduling issues, retries, and data-latency or SLA issues.
• Optimize Airflow DAGs and orchestration workflows to improve reliability, execution time, recoverability, and operational efficiency.
• Troubleshoot pipeline failures, data latency, performance degradation, configuration problems, and infrastructure-related issues.
• Work extensively with Cloud Spanner, BigQuery, Dataflow, Pub/Sub, Cloud Composer (Apache Airflow), Cloud Storage, Cloud Monitoring and Logging, IAM, and related GCP services.
• Monitor platform health and proactively improve reliability, scalability, performance, and operational efficiency.
• Optimize existing pipelines and workloads to improve data refresh times, throughput, query performance, and platform stability.
• Support platform, infrastructure, configuration, and dependency upgrades while maintaining production stability and compliance.
• Perform root-cause analysis for recurring production issues and implement sustainable fixes.
• Support IAM, access controls, monitoring, alerting, logging, and operational governance.
• Collaborate with client and cross-functional Data Engineering, BI/Analytics, Application Engineering, Infrastructure, and Platform teams on production issues and enhancements.
• Adapt to established client-specific engineering, security, compliance, review, and operational processes.
• Review existing architectures and recommend incremental improvements without unnecessarily redesigning stable production systems.
• Create and maintain technical documentation, operational runbooks, troubleshooting guides, and platform support procedures.

You’ll Thrive in This Role If You Have

• 3-7+ years of experience in Data Engineering, Cloud Engineering, Platform Engineering, or a related role.
• Strong hands-on experience building, supporting, or maintaining production workloads on Google Cloud Platform (GCP).
• Strong experience with BigQuery and Cloud Spanner.
• Hands-on experience with Dataflow, Pub/Sub, batch/streaming data pipelines, and Cloud Composer / Apache Airflow.
• Strong Python and SQL skills.
• Good understanding of GCP IAM, service accounts, permissions, monitoring, logging, alerting, and production operations.
• Experience troubleshooting complex production environments and performing root-cause analysis.
• Understanding of data ingestion, transformation, orchestration, data quality, performance optimization, and reliability.
• Ability to quickly understand existing systems, codebases, pipelines, configurations, and client-specific tools and workflows.
• Strong communication and collaboration skills across engineering and business teams.

Preferred Qualifications

• Experience supporting large-scale, business-critical data platforms with demanding availability, reliability, and data-freshness requirements.
• App Engine and other GCP-hosted applications.
• Cloud Run, GKE, or other GCP application services.
• CI/CD and DevOps practices on GCP.
• Infrastructure as Code, particularly Terraform.
• Data observability and automated data-quality monitoring.
• Supporting AI/ML, GenAI, or LLM-based applications running on GCP, including Vertex AI.
• Ability to quickly learn and operate within enterprise-specific analytics, engineering, and operational tooling.

The expected salary range for this position is $60,000 - $110,000 USD per year, based on experience, skills, and qualifications.

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