Sr. Data Engineer
About this Position
As a Senior Data Engineer at Globalization Partners, you will be responsible for designing, building, and maintaining scalable data infrastructure and pipelines that power our global platform. You'll work with cutting-edge technologies to process vast amounts of data, ensuring reliability, performance, and quality across our data ecosystem.
What You Can Expect to Do:
Design and implement robust data pipelines for both batch and streaming data processing, handling structured and unstructured data from various sources across our global platform ecosystem.
Build and optimize ETL/ELT processes that efficiently transform and load data into our data warehouse and analytics platforms, ensuring data quality and consistency throughout the pipeline.
Develop scalable data architectures using cloud-native technologies and modern data platforms, contributing to architectural decisions that support business growth and technical excellence.
Collaborate with cross-functional teams including Data Scientists, Analytics Engineers, Product Managers, and Engineering teams to understand data requirements and deliver solutions that enable data-driven decision making.
Implement data quality frameworks and monitoring systems to ensure data accuracy, completeness, and reliability across all data assets, proactively identifying and resolving data issues.
Optimize data platform performance by analyzing query patterns, implementing efficient data models, and fine-tuning system configurations to handle growing data volumes and user demands.
Maintain and enhance data infrastructure including data warehouses, lakes, and processing clusters, ensuring high availability, security, and cost-effectiveness of our data systems.
Champion engineering best practices including code reviews, automated testing, CI/CD processes, and documentation to maintain high-quality, maintainable data solutions.
Support data governance initiatives by implementing cataloging, lineage tracking, and access controls that enable secure and compliant data usage across the organization.
Mentor junior engineers and contribute to the team's technical growth by sharing knowledge, conducting code reviews, and promoting a culture of continuous learning and innovation.
What We Are Looking For:
6+ years of experience in data engineering with a strong track record of building and maintaining production data systems at scale.
Expert-level proficiency in Python with experience in data processing libraries (PySpark, Pandas, NumPy)
Advanced SQL skills with deep understanding of query optimization, indexing strategies, and performance tuning across various database systems.
Hands-on experience with modern data platforms such as Databricks, Snowflake, or cloud-native solutions (AWS Redshift, Google BigQuery, Azure Synapse) including best practices for enterprise deployments.
Strong background in ETL/ELT processes with experience using tools like Apache Airflow, dbt, Fivetran, or similar orchestration and transformation frameworks.
Proficiency with cloud platforms (preferably AWS) including services like S3, Lambda, Glue, EMR, Kinesis, and understanding of cloud-native data architectures.
Experience with streaming data technologies such as Apache Kafka, AWS Kinesis, or similar real-time data processing systems.
Knowledge of data modeling techniques including dimensional modeling, data vault methodology, and modern approaches like wide tables and denormalization strategies.
Familiarity with data governance tools such as Atlan, Alation, Informatica, or Collibra, and experience implementing data cataloging and lineage tracking.
Understanding of data quality tools and practices with experience using platforms like Monte Carlo, Great Expectations, or custom quality frameworks.
Experience with Infrastructure as Code (Terraform, CloudFormation).
Strong analytical and problem-solving skills with ability to troubleshoot complex data issues, optimize performance, and design solutions for ambiguous requirements.
Excellent communication skills with experience collaborating with technical and non-technical stakeholders to translate business requirements into technical solutions.
Bachelor's degree in Computer Science, Engineering, or related field; advanced degrees or equivalent professional experience are valued.
Fluent in English both verbal and written, with ability to work effectively in a global, distributed team environment.
We will consider for employment all qualified applicants who meet the inherent requirements for the position. Please note that background checks are required, and this may include criminal record checks.
Individuals with disabilities are encouraged to apply for these positions.
Sr. Data Engineer
About this Position
As a Senior Data Engineer at Globalization Partners, you will be responsible for designing, building, and maintaining scalable data infrastructure and pipelines that power our global platform. You'll work with cutting-edge technologies to process vast amounts of data, ensuring reliability, performance, and quality across our data ecosystem.
What You Can Expect to Do:
Design and implement robust data pipelines for both batch and streaming data processing, handling structured and unstructured data from various sources across our global platform ecosystem.
Build and optimize ETL/ELT processes that efficiently transform and load data into our data warehouse and analytics platforms, ensuring data quality and consistency throughout the pipeline.
Develop scalable data architectures using cloud-native technologies and modern data platforms, contributing to architectural decisions that support business growth and technical excellence.
Collaborate with cross-functional teams including Data Scientists, Analytics Engineers, Product Managers, and Engineering teams to understand data requirements and deliver solutions that enable data-driven decision making.
Implement data quality frameworks and monitoring systems to ensure data accuracy, completeness, and reliability across all data assets, proactively identifying and resolving data issues.
Optimize data platform performance by analyzing query patterns, implementing efficient data models, and fine-tuning system configurations to handle growing data volumes and user demands.
Maintain and enhance data infrastructure including data warehouses, lakes, and processing clusters, ensuring high availability, security, and cost-effectiveness of our data systems.
Champion engineering best practices including code reviews, automated testing, CI/CD processes, and documentation to maintain high-quality, maintainable data solutions.
Support data governance initiatives by implementing cataloging, lineage tracking, and access controls that enable secure and compliant data usage across the organization.
Mentor junior engineers and contribute to the team's technical growth by sharing knowledge, conducting code reviews, and promoting a culture of continuous learning and innovation.
What We Are Looking For:
6+ years of experience in data engineering with a strong track record of building and maintaining production data systems at scale.
Expert-level proficiency in Python with experience in data processing libraries (PySpark, Pandas, NumPy)
Advanced SQL skills with deep understanding of query optimization, indexing strategies, and performance tuning across various database systems.
Hands-on experience with modern data platforms such as Databricks, Snowflake, or cloud-native solutions (AWS Redshift, Google BigQuery, Azure Synapse) including best practices for enterprise deployments.
Strong background in ETL/ELT processes with experience using tools like Apache Airflow, dbt, Fivetran, or similar orchestration and transformation frameworks.
Proficiency with cloud platforms (preferably AWS) including services like S3, Lambda, Glue, EMR, Kinesis, and understanding of cloud-native data architectures.
Experience with streaming data technologies such as Apache Kafka, AWS Kinesis, or similar real-time data processing systems.
Knowledge of data modeling techniques including dimensional modeling, data vault methodology, and modern approaches like wide tables and denormalization strategies.
Familiarity with data governance tools such as Atlan, Alation, Informatica, or Collibra, and experience implementing data cataloging and lineage tracking.
Understanding of data quality tools and practices with experience using platforms like Monte Carlo, Great Expectations, or custom quality frameworks.
Experience with Infrastructure as Code (Terraform, CloudFormation).
Strong analytical and problem-solving skills with ability to troubleshoot complex data issues, optimize performance, and design solutions for ambiguous requirements.
Excellent communication skills with experience collaborating with technical and non-technical stakeholders to translate business requirements into technical solutions.
Bachelor's degree in Computer Science, Engineering, or related field; advanced degrees or equivalent professional experience are valued.
Fluent in English both verbal and written, with ability to work effectively in a global, distributed team environment.
We will consider for employment all qualified applicants who meet the inherent requirements for the position. Please note that background checks are required, and this may include criminal record checks.
Individuals with disabilities are encouraged to apply for these positions.