Company: Toptal
Country: United States
Type: Remote
Employment: Full-time
Description:
Headquarters:
Summary General information The role spans cloud-based data architecture, database performance, pipeline automation, and support for data scientists, researchers, and internal business units. The environment includes AWS-based infrastructure and a mix of structured and unstructured data sources. Tasks and Deliverables Required experience Engagement highlights
We are seeking a Data Engineer to support the development of a Data Intelligence Platform. This role focuses on data modeling, data services, data pipelines, and cloud-based data infrastructure for reporting, analytics, and data science.
This Data Engineer will support data-related operations across a broader Data Intelligence Platform team. The work includes building and consuming web services, integrating search technologies, supporting personalization and recommendation engines, and applying data engineering best practices across the platform.
- Participate in the architecture design and implementation of high-performance, scalable, and optimized data solutions.
- Create data models from scratch using strong SQL fundamentals.
- Write and optimize in-application SQL statements.
- Ensure the performance, security, and availability of databases.
- Prepare documentation and technical specifications.
- Handle database procedures such as upgrades, backups, recovery, and migration.
- Profile server resource usage and optimize configurations as necessary.
- Design, build, and automate the deployment of data pipelines and applications.
- Integrate data from on-premise databases and external data sources using REST APIs and harvesting tools.
- Collaborate with business units and data science teams on data access, transformation, processing, and reporting needs.
- Support implementation, technical issues, and training related to the data lake ecosystem.
- Work with the team to manage AWS resources, including EMR and ECS clusters.
- Support provisioning, monitoring, configuration, and maintenance of AWS tools.
- Evaluate and promote new cloud technologies that improve capabilities and lower operating costs.
- Support automation efforts using Infrastructure as Code with Terraform and CI/CD tools such as Jenkins.
- Work with the team to implement data governance, access control, and security risk reduction.
- 7-9 years of experience designing and developing cloud-based data models, ETL pipelines, and infrastructure.
- Experience working with both structured and unstructured data.
- Strong proficiency with SQL across popular databases.
- Experience optimizing large, complex SQL statements.
- Knowledge of best practices for relational databases.
- Experience configuring database engines and orchestrating clusters.
- Ability to plan resource requirements from high-level specifications.
- Ability to troubleshoot common database issues.
- Experience with Spark, Glue, EMR, and Apache Kafka or AWS Kinesis.
- Experience with version control tools such as Git or Subversion.
- Experience using automated build systems and CI/CD workflows.
- Experience programming in Java, Python, and Scala.
- Knowledge of data structures and algorithms.
- Knowledge of relational, NoSQL, graph, document, key-value, and time-series databases.
- Knowledge of scalable data model design and management.
- Knowledge of ML model deployment.
- Knowledge of AWS cloud platforms.
- Knowledge of TDD and BDD.
- Strong interest in improving software development skills, frameworks, and technologies.
- Opportunity to work across data modeling, data services, and data science within a broader Data Intelligence Platform.
- Exposure to a varied technical environment spanning AWS, ETL pipelines, databases, search technologies, and recommendation systems.
- Direct collaboration with data science teams and internal stakeholders on reporting, transformation, and platform capabilities.
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