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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Proficient in Data Engineering practices with a focus on building and maintaining data pipelines using modern platforms like Snowflake, Azure, and GCP. Strong foundation in Python and SQL, with an understanding of CI/CD, data governance, and agile methodologies.
Highest-signal resume keywords
Data EngineeringPython ProgrammingSQL ProficiencyCloud Platforms (Azure, GCP)Data Warehouse Technologies (Snowflake)
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 DevelopmentSQLPythonData ModellingOrchestration ToolsCI/CD PracticesAutomated TestingData GovernanceData QualityData Security
Soft Skills
Strong Communication SkillsProblem-SolvingTeam CollaborationOpenness to FeedbackOwnership of Tasks
Tools & Technologies
SnowflakeAzureGCPDbtPrefectAirflowADF
Certifications & Qualifications
Degree in Computer ScienceDegree in EngineeringDegree in MathematicsDegree in Data Science
Industry Keywords
Data EngineeringAgile PracticesData AnalyticsData LifecycleIncremental DeliveryProofs of ConceptStructured DataSemi-Structured DataCross-Functional TeamsDocumentation
Tech Stack
Tools & technologiesAirflowAzureCloudGoogle Cloud PlatformPythonSQL
About the role
Key responsibilities & impact- Support the build and maintenance of data pipelines and data products across the data lifecycle
- Implement well-defined data engineering tasks under the guidance of senior and Lead Data Engineers
- Help ensure data is accurate and accessible for analytics and reporting
- Contribute to incremental delivery of business value using agile practices
- Assist with Proofs of Concept and experimentation
- Learn and apply best practices in cloud data engineering and DevOps, including CI/CD and testing
- Develop using modern platforms such as Snowflake, Azure, and GCP
- Write clear, maintainable code using Python, SQL, dbt, and orchestration tools
- Take part in code reviews and act on feedback
- Assist with monitoring and troubleshooting of pipelines
- Work closely with Data Engineers, Data Scientists, and stakeholders
- Support Product Owners in the delivery of data solutions
- Participate in the Data Engineering Chapter and knowledge sharing
- Help business users with data understanding
- Follow data governance, quality, and security best practices
- Support validation, lineage, and monitoring within pipelines
- Contribute to documentation of data products and pipelines
- Develop awareness of cost-efficient solution design
- Support optimisation of pipelines for performance and scalability
- Assist with monitoring of platform usage
Requirements
What you’ll need- Some experience or exposure to Data Engineering, software development, or analytics (typically 1–2 years)
- Working knowledge of SQL
- Basic programming experience, ideally in Python
- Awareness of cloud platforms such as Azure or GCP
- Awareness of data warehouse technologies such as Snowflake
- Familiarity with source control and an interest in CI/CD practices and automated testing
- Basic understanding of data modelling concepts (OLTP, OLAP)
- Familiarity with structured and semi-structured data
- Exposure to SQL databases
- Willingness to take ownership of assigned tasks and deliver them to completion
- Pragmatic problem-solving approach
- Interest in working in agile environments
- Strong communication skills
- Ability to work in cross-functional teams
- Openness to feedback and coaching
- Degree in Computer Science, Engineering, Mathematics, Data Science, or a related field is desirable
- Exposure to orchestration tools such as Prefect, Airflow, or ADF is beneficial
- Exposure to dbt or similar transformation tools is beneficial
Benefits
Comp & perks- Hybrid work arrangement
- Learning and development through guidance, feedback, coaching, and knowledge sharing
- Participation in the Data Engineering Chapter
- Opportunities to work with modern cloud technologies and engineering practices
- Agile working practices