MLabs
Senior Data Engineer - AI-First Fintech Platform
Location:
Remote - Fully Remote - Across Europe
Compensation:
$120K - $140K
We are a rapidly growing fintech and crypto platform undergoing an AI-first transformation. We are seeking a strategic, high-impact, and high-ownership Senior Data Engineer to build the foundational data infrastructure that powers our cutting-edge AI features.
You will report directly to the CTO and work closely with our Machine Learning (ML) team to consolidate and govern our data ecosystem (including PostgreSQL, Kafka, BigQuery, and GCS) into a clean, governed, and ML-ready platform. Your contributions will directly enable critical AI functionality across our product suite.
This role is responsible for the end-to-end design, implementation, and governance of our core data platform, ensuring high performance and readiness for ML applications.
Responsibilities
Build and consolidate the foundational data platform, ensuring data from various sources (PostgreSQL, Kafka) is accurately captured and processed into our cloud data warehouse
Design and implement robust, resilient batch and real-time data pipelines using streaming platforms and Change Data Capture (CDC) tools
Apply expert-level SQL and tools like dbt to build and maintain dimensional models (fact/dimension tables) optimized for analytics, reporting, and Machine Learning feature creation
Implement and enforce strict data governance policies, including PII tagging, column-level security, and access controls. Implement automated data quality monitoring with checks and alerting
Optimize the performance of our data warehouse (e.g., BigQuery) through techniques like partitioning, clustering, and advanced query optimization
Implement and maintain full observability of the data platform, focusing on data freshness monitoring, schema change detection, and pipeline health dashboards
Work closely with the ML team and CTO to structure data specifically to enable and accelerate the development of new AI-driven features
Requirements
Strong hands-on experience with Google Cloud Platform (GCP) data services (e.g., BigQuery, Dataflow, Cloud Storage, DataStream, AlloyDB/CloudSQL)
Expert-level SQL proficiency and significant experience with data modeling tools like dbt for transformation and testing
Hands-on experience with streaming platforms (Kafka, Kafka Connect) and an understanding of Change Data Capture (CDC) tools (Debezium or similar)
Proven experience building dimensional models (fact/dimension tables) for analytics and ML features
Practical experience implementing data governance measures (PII tagging, security, access controls)
Experience with implementing automated data quality monitoring and setting up data observability (freshness, schema changes, health dashboards)
Experience optimizing data warehouse performance (e.g., BigQuery partitioning, clustering, query tuning)
Nice to Have
Experience with Feature Store architecture and understanding ML feature serving patterns (real-time vs. batch)
Prior work within financial services or regulated data environments
Familiarity with the Vertex AI ecosystem or Apache Beam/Dataflow transformations
Knowledge of vector databases or semantic search concepts
Background collaborating directly with ML/data science teams
Benefits
Competitive salary plus stock options (equity package)
Option for Full-Time Employment (FTE through EoR) or B2B Contract (candidate preference)
Private dental and health insurance (for FTE employees)
30 days of paid holidays (excluding bank holidays) (for FTE employees)
Provision of the best necessary tech for your role
100% remote work option available, or the choice to work from the office
Ability to work abroad for up to 4 months a year
Leading position offering huge impact, autonomy, and ownership
Notes:
Note: Candidates choosing the B2B contract option do not receive paid holiday or insurance
Referrals increase your chances of interviewing at MLabs by 2x
#J-18808-Ljbffr
Remote - Fully Remote - Across Europe
Compensation:
$120K - $140K
We are a rapidly growing fintech and crypto platform undergoing an AI-first transformation. We are seeking a strategic, high-impact, and high-ownership Senior Data Engineer to build the foundational data infrastructure that powers our cutting-edge AI features.
You will report directly to the CTO and work closely with our Machine Learning (ML) team to consolidate and govern our data ecosystem (including PostgreSQL, Kafka, BigQuery, and GCS) into a clean, governed, and ML-ready platform. Your contributions will directly enable critical AI functionality across our product suite.
This role is responsible for the end-to-end design, implementation, and governance of our core data platform, ensuring high performance and readiness for ML applications.
Responsibilities
Build and consolidate the foundational data platform, ensuring data from various sources (PostgreSQL, Kafka) is accurately captured and processed into our cloud data warehouse
Design and implement robust, resilient batch and real-time data pipelines using streaming platforms and Change Data Capture (CDC) tools
Apply expert-level SQL and tools like dbt to build and maintain dimensional models (fact/dimension tables) optimized for analytics, reporting, and Machine Learning feature creation
Implement and enforce strict data governance policies, including PII tagging, column-level security, and access controls. Implement automated data quality monitoring with checks and alerting
Optimize the performance of our data warehouse (e.g., BigQuery) through techniques like partitioning, clustering, and advanced query optimization
Implement and maintain full observability of the data platform, focusing on data freshness monitoring, schema change detection, and pipeline health dashboards
Work closely with the ML team and CTO to structure data specifically to enable and accelerate the development of new AI-driven features
Requirements
Strong hands-on experience with Google Cloud Platform (GCP) data services (e.g., BigQuery, Dataflow, Cloud Storage, DataStream, AlloyDB/CloudSQL)
Expert-level SQL proficiency and significant experience with data modeling tools like dbt for transformation and testing
Hands-on experience with streaming platforms (Kafka, Kafka Connect) and an understanding of Change Data Capture (CDC) tools (Debezium or similar)
Proven experience building dimensional models (fact/dimension tables) for analytics and ML features
Practical experience implementing data governance measures (PII tagging, security, access controls)
Experience with implementing automated data quality monitoring and setting up data observability (freshness, schema changes, health dashboards)
Experience optimizing data warehouse performance (e.g., BigQuery partitioning, clustering, query tuning)
Nice to Have
Experience with Feature Store architecture and understanding ML feature serving patterns (real-time vs. batch)
Prior work within financial services or regulated data environments
Familiarity with the Vertex AI ecosystem or Apache Beam/Dataflow transformations
Knowledge of vector databases or semantic search concepts
Background collaborating directly with ML/data science teams
Benefits
Competitive salary plus stock options (equity package)
Option for Full-Time Employment (FTE through EoR) or B2B Contract (candidate preference)
Private dental and health insurance (for FTE employees)
30 days of paid holidays (excluding bank holidays) (for FTE employees)
Provision of the best necessary tech for your role
100% remote work option available, or the choice to work from the office
Ability to work abroad for up to 4 months a year
Leading position offering huge impact, autonomy, and ownership
Notes:
Note: Candidates choosing the B2B contract option do not receive paid holiday or insurance
Referrals increase your chances of interviewing at MLabs by 2x
#J-18808-Ljbffr