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. Youll work with cutting-edge technologies to process vast amounts of data, ensuring reliability, performance, and quality across our data ecosystem
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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 teams 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.
- Bachelors 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.
