Senior Data Engineer

Mapon

. Build and own the data warehouses behind Mapon’s data analysis and AI solutions .

Posted 11/10/2026full-timeRiga • LatviaSenior💰 €4,500 per monthWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and managing data warehouses and ETL/ELT pipelines, with a strong focus on data quality, security, and compliance with GDPR. Proficient in collaborating with cross-functional teams to ensure effective data utilization for analytics and AI solutions.

Highest-signal resume keywords

Data Engineering ExperienceETL/ELT Pipeline DevelopmentSQL, DAX, Python ProficiencyData Warehouse DesignGDPR Compliance Understanding

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DesignData Warehouse ManagementSQLDAXPythonETL/ELT DevelopmentData Structure UnderstandingPerformance TuningData IntegrationData Quality Checks

Soft Skills

CollaborationCommunication

Tools & Technologies

AirflowDagsterGitLabHubSpotMicrosoft Dynamics 365MySQLMariaDBPostgreSQL

Industry Keywords

Data SecurityPrivacy ComplianceAI SolutionsData AnalyticsSaaS Integration

Tech Stack

Tools & technologies

AirflowCloudERPETLMariaDBMySQLPostgresPythonSQL

About the role

Key responsibilities & impact

Build and own the data warehouses behind Mapon’s data analysis and AI solutions
Design, implement, manage and monitor data pipelines, replications, transformations, data warehouses and purpose-specific data structures
Organise data into bronze, silver and gold layers
Design, set up, monitor and administer analytics data warehouses and dedicated replica datasets separate from production
Design and build ETL/ELT pipelines using raw, cleaned/conformed and business-ready data layers
Monitor, refactor and optimise data replication processes
Ingest data from production databases, CRM, HubSpot, Microsoft Dynamics 365, Moneo, Emfino and other systems
Work with the existing data warehouse and BI team so reports are built on the gold layer
Make analytics data useful and available to AI tools
Build monitoring, data quality checks, lineage and documentation
Define access control, PII handling and retention with Legal and the DPO in line with GDPR and customer data processing rules
Help choose technologies, contribute to target architecture, and estimate effort and cost
Support analysts and Product Managers in using data effectively
Report to the Software Development Technical Manager and collaborate with BI, Finance, Sales, Product and Infrastructure teams

Requirements

What you’ll need

5+ years of hands-on data engineering experience, including building production ETL/ELT pipelines
Understanding of data structures, including relational databases, denormalised structures, time-series datasets and files
Understanding of data structures suitable for AI solutions
Practical experience preparing data for AI and LLM-based analytics tools
Strong SQL, DAX and Python, or equivalent languages
Experience with data warehouse or lakehouse design and a layered approach
Experience with large-scale relational databases such as MySQL, MariaDB or PostgreSQL, including replication and performance tuning
Experience with workflow orchestration such as Airflow, Dagster or similar
Experience with version control and CI/CD, including GitLab
Experience integrating data from APIs, SaaS tools such as CRM and ERP systems, and databases
Comfort working with on-premises infrastructure and cloud environments
Understanding of data security and privacy, including GDPR
Fluent English
Two references from previous workplaces for the background check

Benefits

Comp & perks

Paid lunches and fruit in the office
Personalised employee benefits after the probation period, including health insurance, mental-health support, dental care and massage courses
Additional sports programme or employer contributions to your third-pillar pension plan through Indexo
Additional paid holidays, including your birthday
Paid study leave
Wellness days without needing a sick-leave certificate
Access to paid AI tools such as Claude, ChatGPT, Gemini and others
Annual learning budget for seminars, courses, books and other development opportunities
Free parking at the office
Flexible working hours, with the option to begin your workday any time before 11:00
Opportunity to work outside Latvia for up to 90 days per year
Hybrid work from the Riga office and partly from home
Dedicated budget for team-building events
Referral bonus when a recommended candidate joins Mapon
Mentor bonus when a supported new colleague reaches the two-month milestone
Additional bonuses for special occasions and important life events
Paid participation in the Riga Marathon
Interest groups and activities within the Draugiem Group community