OneSix
Data Engineer
Remote Data Engineering role with clear candidate location fit.
PostedJul 2, 2026
Eligible countries9 accepted countries
Seniority signalSenior
Work settingRemote
Accepted candidate locations
Role overview
Data Engineer
Requirements and responsibilities
Readable role content extracted into sections for faster review.
Core Responsibilities
- Data Engineering & DevelopmentDevelop and maintain robust data integration pipelines (ETL and ELT) to process large volumes of financial data across cloud and on-premise environments.Design and implement efficient data models, data warehouses, and data lakes optimized for financial reporting and analytics.Optimize performance, scalability, and reliability of data storage and processing systems.Monitor data pipelines and troubleshoot issues promptly to minimize downtime.
- Develop and maintain robust data integration pipelines (ETL and ELT) to process large volumes of financial data across cloud and on-premise environments.
- Design and implement efficient data models, data warehouses, and data lakes optimized for financial reporting and analytics.
- Optimize performance, scalability, and reliability of data storage and processing systems.
- Monitor data pipelines and troubleshoot issues promptly to minimize downtime.
Data Engineering & Development
- Develop and maintain robust data integration pipelines (ETL and ELT) to process large volumes of financial data across cloud and on-premise environments.
- Design and implement efficient data models, data warehouses, and data lakes optimized for financial reporting and analytics.
- Optimize performance, scalability, and reliability of data storage and processing systems.
- Monitor data pipelines and troubleshoot issues promptly to minimize downtime.
Core Responsibilities
- Collaboration & Quality AssuranceCollaborate with data scientists, analysts, and engineers to ensure data availability, quality, and integrity.Participate in code reviews, automated testing, and deployment processes to maintain high-quality data engineering standards.
- Collaborate with data scientists, analysts, and engineers to ensure data availability, quality, and integrity.
- Participate in code reviews, automated testing, and deployment processes to maintain high-quality data engineering standards.
- Compliance & SecurityEnsure compliance with industry-specific regulatory requirements for data security and privacy.
- Ensure compliance with industry-specific regulatory requirements for data security and privacy.
- Technical Leadership & DeliveryDemonstrate in-depth technical capabilities and professional knowledge.Define the architecture, design solutions, and support test and implementation of business intelligence and software applications.
- Demonstrate in-depth technical capabilities and professional knowledge.
- Define the architecture, design solutions, and support test and implementation of business intelligence and software applications.
Details
- Collaborate with data scientists, analysts, and engineers to ensure data availability, quality, and integrity.
- Participate in code reviews, automated testing, and deployment processes to maintain high-quality data engineering standards.
- Ensure compliance with industry-specific regulatory requirements for data security and privacy.
- Demonstrate in-depth technical capabilities and professional knowledge.
- Define the architecture, design solutions, and support test and implementation of business intelligence and software applications.
- Engage with internal leadership and teams to deliver solutions and drive projects.
- Focus on the business value of solutions while leveraging technology to solve data challenges in financial services.
Core Responsibilities
- Stakeholder EngagementEngage with internal leadership and teams to deliver solutions and drive projects.Focus on the business value of solutions while leveraging technology to solve data challenges in financial services.
- Engage with internal leadership and teams to deliver solutions and drive projects.
- Focus on the business value of solutions while leveraging technology to solve data challenges in financial services.
Qualifications
- Prior experience working in either Data Warehousing or Business Intelligence, with exposure to architecting and/or building cloud-based data platforms considered a significant advantage
- Experience working with major cloud and on-premise database technologies such as Snowflake, Redshift, BigQuery, Azure Synapse, SQL Server, Oracle, Postgres, and/or MySQL
- Experience with one or more commercial cloud platforms — AWS, Azure, or Google Cloud
- Technical experience in ETL/ELT tools such as Fivetran, DBT, Matillion, SSIS, Coalesce, Talend, Informatica, or Rivery
- Expertise with Business Intelligence/Data Visualization tools such as Power BI, Tableau, Looker, Sigma, Pyramid Analytics, ThoughtSpot, Sisense, or Qlik
- Experience designing and implementing data models for applications and/or reporting purposes
- Strong desire to work hands-on developing Data Lakes, Data Warehouses, and other performance management solutions across various industries and functional disciplines
- Demonstrated problem-solving and quantitative skills, combined with excellent written and verbal communication skills
- Experience with real-time data processing frameworks such as Kafka, Spark, or similar.
- Background working with financial datasets, including transactional data, risk metrics, or compliance reports.
- Familiarity with automated testing, CI/CD pipelines, and infrastructure as code.
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