Senior Data Engineer, Google Cloud Platform (GCP)

West Monroe•New York City, NY

45d•$119,500 - $161,700

About The Position

Are you ready to make an impact? As a Senior Data Engineer , you will work with clients and internal teams to develop scalable, high-performance data solutions. You will focus on building modern data pipelines, implementing cloud-native architectures, and ensuring data quality and reliability. This role requires strong technical expertise, problem-solving skills, and the ability to collaborate in a fast-paced consulting environment.

Requirements

5+ years of experience in data engineering or related roles, with hands-on experience in designing and implementing data pipelines and architectures.
Strong expertise in cloud platforms, particularly Google Cloud Platform (GCP), with experience using services such as BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage.
Proficiency in building ETL/ELT workflows and data pipelines using tools like Apache Beam, Cloud Composer, or Cloud Data Fusion.
Experience with real-time data processing and streaming technologies such as Pub/Sub, Kafka, or Spark Streaming.
Solid understanding of SQL for data modeling, querying, and optimization.
Strong programming skills in Python or Java, with experience in developing reusable and scalable codebases.
Familiarity with infrastructure as code (IaC) tools like Terraform or Deployment Manager for provisioning cloud resources.
Knowledge of data governance, security, and compliance best practices, including IAM roles, encryption, and VPC Service Controls.
Experience with CI/CD pipelines for data workflows and DevOps practices.
Proven ability to work collaboratively in a team environment and communicate effectively with technical and non-technical stakeholders.

Nice To Haves

GCP certifications such as Professional Data Engineer or Professional Cloud Architect are preferred.
Experience with other cloud platforms (AWS, Azure) is a plus.
Familiarity with machine learning workflows and tools like Vertex AI is a plus.
Strong problem-solving skills and ability to troubleshoot complex data pipeline issues.
Travel to client site as needed (30% to 50%).

Responsibilities

Design and develop robust, scalable, and efficient data pipelines using modern tools and frameworks.
Build and optimize ETL/ELT workflows for ingesting, transforming, and storing structured and unstructured data.
Implement data architectures on cloud platforms, particularly Google Cloud Platform (GCP), leveraging services such as Dataflow, BigQuery Dataform, and Data Fusion
Develop real-time data processing solutions using streaming technologies like Apache Beam and Pub/Sub.
Collaborate with data architects and business stakeholders to design data models optimized for analytics, reporting, and machine learning.
Ensure data quality, security, and governance by implementing best practices and using tools like Cloud DLP, IAM, and Dataplex.
Monitor, troubleshoot, and optimize data pipelines for performance and cost efficiency using tools like Cloud Monitoring and Cloud Logging.
Implement CI/CD pipelines for data workflows using tools like Cloud Build, GitHub Actions, or Terraform.
Write clean, maintainable, and well-documented code in Python, Java, or other programming languages.
Serve as a technical mentor to junior data engineers and contribute to knowledge-sharing initiatives within the team.
Collaborate with cross-functional teams to deliver end-to-end data solutions aligned with business objectives.

Benefits

Employees (and their families) are covered by medical, dental, vision, and basic life insurance.
Employees are able to enroll in our company’s 401k plan, purchase shares from our employee stock ownership program and be eligible to receive annual bonuses.
Employees will also receive unlimited flexible time off and ten paid holidays throughout the calendar year.
Eligibility for ten weeks of paid parental leave will also be available upon hire date.

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