Data Engineer

Mackin Talent

. Develop, evaluate, test and maintain architectures and data solutions .

Posted 9/28/2026contractLondon • United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and maintaining scalable data management systems, including building production data pipelines and optimizing SQL for large datasets. Proficient in data transformation using Python and experienced in collaborating with cross-functional teams to achieve project goals.

Highest-signal resume keywords

SQL Performance TuningPython Data TransformationETL Process AutomationDistributed Query Engine ExperienceWorkflow Scheduler Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentSQL OptimizationETL ProcessesData Quality ChecksData ModellingBatch ETL PipelinesAlgorithm DevelopmentPredictive ModelingData Solutions ArchitectureData Management Systems

Soft Skills

Team CollaborationExcellent Communication SkillsIndependent Work Ability

Tools & Technologies

AirflowGitMicrosoft SharePointPrestoSparkHive

Certifications & Qualifications

Six SigmaCBPPBPMISO 20000ITILCMMI

Industry Keywords

Data Quality FrameworksPipeline ObservabilityBusiness RequirementsVersion ControlChange Management

Tech Stack

Tools & technologies

AirflowETLPythonSparkSQL

About the role

Key responsibilities & impact

Develop, evaluate, test and maintain architectures and data solutions
Execute plans, policies, and practices that control, protect, deliver, and enhance the value of organizational data assets
Design, construct, install, test and maintain highly scalable data management systems
Ensure systems meet business requirements and industry practices
Design, implement, automate and maintain large-scale enterprise data ETL processes
Build high-performance algorithms, prototypes, predictive models and proofs of concept
Build, test and maintain batch ETL pipelines for assigned datasets
Implement changes to existing pipelines and tables, including backfills and schema updates
Write and optimize SQL for large-scale datasets
Investigate and fix data quality issues
Add and maintain data quality checks, tests and pipeline documentation
Produce prototypes and exploratory analyses as requested
Participate in code reviews and follow team conventions for version control, deployment and change management
Collaborate with data architects, modelers and IT team members on project goals

Requirements

What you’ll need

Bachelor's degree in computer science, engineering, or a related technical field, or equivalent practical experience
5+ years building production data pipelines
Strong SQL, including performance tuning on large tables
Python for data transformation and pipeline orchestration
Experience with a distributed query engine (Presto, Spark, Hive or similar)
Experience with a workflow scheduler (Airflow or similar)
Comfortable working in a code review based workflow with Git
Ability to work as part of a team, independently, or with minimal direction
Excellent written, presentation, and verbal communication skills
Experience collaborating with data architects, modelers and IT team members on project goals
Strong PC skills including knowledge of Microsoft SharePoint
Experience with data modelling for analytics (dimensional or wide-table patterns) is nice to have
Experience building dashboards or working with BI tooling is nice to have
Experience with data quality frameworks and pipeline observability is nice to have
Process certification, such as Six Sigma, CBPP, BPM, ISO 20000, ITIL, CMMI

Benefits

Comp & perks

Healthcare contribution and inclusion in company pension scheme
Work laptop and phone
25 days annual leave (pro-rata) plus paid bank holidays
Potential for career progression for top performers