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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing scalable data pipelines and ETL/ELT processes, with a strong focus on data governance, quality, and compliance. Proficient in leveraging modern data platforms and tools to deliver trusted data products for analytics and operational use cases.
Highest-signal resume keywords
SnowflakeELT/ETL Pipeline DevelopmentAdvanced SQLData GovernanceDimensional Modelling
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data Pipeline DesignData TransformationData Quality FrameworksAutomated TestingDimensional ModellingAPI IntegrationEvent-Driven ArchitectureReverse ETLMonitoring SolutionsInfrastructure as Code
Soft Skills
Problem-SolvingAnalytical ThinkingCommunicationMentoringCollaboration
Tools & Technologies
FivetranDbtGitCI/CDAzureAWSGCPDatabricksRedshiftBigQuery
Industry Keywords
Data GovernanceMetadata ManagementSecurity CompliancePrivacy Best PracticesOperational Workloads
Tech Stack
Tools & technologiesAmazon RedshiftAWSAzureBigQueryETLGoogle Cloud PlatformSQL
About the role
Key responsibilities & impact- Design, develop, and optimise scalable data pipelines using ELT tools, APIs, databases, and event-based architectures
- Lead integration of new data sources into Snowflake and define reusable ingestion patterns and engineering standards
- Design and implement ETL/ELT processes for large-scale analytics, AI, and operational workloads
- Define ingestion patterns for incremental, CDC, full refresh, and near real-time processing
- Design and operate reverse ETL pipelines delivering trusted data products to operational systems, applications, and APIs
- Improve platform reliability, performance, observability, and cost optimisation
- Design and maintain scalable dbt data transformation frameworks
- Develop and maintain dimensional models, including fact, dimension, snapshot, and semantic data structures
- Define modelling standards, naming conventions, and data-platform best practices
- Implement automated testing, data quality frameworks, lineage tracking, and monitoring solutions
- Design and maintain trusted datasets and data products for analytics, AI, self-service, and operational use cases
- Collaborate with stakeholders to translate business requirements into scalable technical solutions
- Lead troubleshooting and resolution of complex data platform, pipeline, and performance issues
- Drive data governance initiatives covering data ownership, metadata management, lineage, schema evolution, and data contracts
- Maintain engineering documentation, technical standards, architectural patterns, and operational runbooks
- Mentor Associate and Mid-Level Data Engineers through code reviews, technical coaching, and knowledge sharing
- Evaluate emerging technologies and recommend platform improvements
- Ensure data solutions comply with security, privacy, governance, and regulatory requirements
Requirements
What you’ll need- Strong experience with modern data platforms such as Snowflake, Databricks, Redshift, BigQuery, or similar technologies
- Extensive experience building and operating ELT/ETL pipelines in production environments
- Advanced SQL skills for querying, transforming, optimising, and analysing large datasets
- Strong hands-on experience with data ingestion tools such as Fivetran and API-based integration patterns
- Strong experience with dbt for data transformation, testing, documentation, and dimensional modelling
- Deep understanding of dimensional modelling concepts, including facts, dimensions, metrics, snapshots, and semantic layers
- Experience implementing data quality, observability, monitoring, and lineage solutions
- Experience designing batch, event-driven, and near real-time data architectures
- Strong understanding of reverse ETL patterns and operational data delivery
- Experience with Git, CI/CD pipelines, automated testing, and Infrastructure as Code
- Strong knowledge of Azure, AWS, or GCP and their data services
- Strong understanding of data governance, metadata management, security, privacy, and compliance best practices
- Excellent problem-solving and analytical thinking skills
- Ability to evaluate technical trade-offs and make architectural decisions balancing scalability, maintainability, performance, and cost
- Strong communication skills and ability to engage effectively with technical and non-technical stakeholders
- Demonstrated experience mentoring engineers and leading technical initiatives
- Ability to work independently while driving alignment across multiple teams and business domains
Benefits
Comp & perks- Long-term fixed-term contract
- Hybrid work model with three days a week in the office
- Equal opportunity employer
- Reasonable accommodations may be made to allow an individual to perform the essential functions of the role successfully
- Career growth opportunities in a fast-paced technology market