We are seeking a talented and driven Data Engineer to join our team. You will be responsible for building and deploying data pipelines, scalable machine learning models and bridging the gap between data science and production systems. You will collaborate with data scientists and software engineers to translate research and prototypes into robust, production-ready solutions.
Job Responsibilities
Develop and maintain infrastructure for enterprise data platforms and machine learning.
Collaborate with business stakeholders to gather requirements and translate them into effective data visualizations and reporting solutions.
Design, build, and maintain scalable and interactive dashboards using BI tools such as Power BI, Tableau, or Looker.
Implement and manage data governance frameworks, including data cataloging, lineage, quality, and access controls using cloud-native tools (e.g., AWS Glue, Azure Purview, Google Cloud Data Catalog).
Data Platform Development \& Management:
Design, develop, and maintain data platforms that support large-scale data ingestion, storage, and processing using cloud-based data infrastructure.
Implement and manage data warehousing and centralized data solutions tailored for asset management.
Evaluate and integrate new data technologies and tools to enhance data platform capabilities.
Data Pipeline Development:
Build and maintain robust and efficient data pipelines for data ingestion, processing, and transformation.
Develop and implement data quality checks and validation processes to ensure data accuracy, timeliness, and consistency.
Utilize ETL/ELT tools and techniques to transform and load data into target systems.
Employing exceptional problem-solving skills, with the ability to see and solve issues before they snowball into problems.
Learn and share knowledge and experience in a multi-disciplinary team.
Job Requirements
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
At least 5 years of experience in data engineering, business intelligence, machine learning engineering, or a related role in a production environment.
Familiarity with data governance frameworks (e.g., DAMA-DMBOK) and regulatory compliance (e.g., GDPR, CCPA).
Hands-on experience in Python and SQL. Experience with other programming languages (e.g., Java, Scala, C++) is a plus.
Experience in best practices such as DataOps and MLOps
Experience with big data technologies and cloud platforms such as BigQuery, Kafka, GCP, AWS and their data engineering and machine learning products and services.
Strong understanding of software development best practices, including version control (Git), testing, and CI/CD.
Excellent communication and organizational skills, and the ability to stay focused on completing tasks and meeting goals within a busy workspace.
Skilled at working in tandem with a team of engineers, or alone as required.
Strong troubleshooting and analytical skills.
Cloud and data certifications are a plus.