Senior Data Engineer

Adaptiq

Location
Remote
Employment
Full-time
Level
Specialist
Category
Data & Analytics
Posted
Deadline

Description

Job Title:

Senior Data Engineer

Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

About the Product:

Our client is a major online gaming operator building a next-generation transactional platform for user account management. This is a greenfield project designed to operate in a highly regulated, high-volume environment and support millions of concurrent users. The platform will process financial transactions in real time and must ensure high availability, sub-second performance, data integrity, security, and full auditability. One of the key engineering challenges is maintaining reliability and performance during extreme traffic spikes and peak events.

The team is looking for a hands-on Data Engineer to help build and maintain scalable and reliable data infrastructure, develop production-grade data pipelines, and work with large volumes of business and transactional data, with a strong focus on data quality, integrity and performance.

About the Role:

You will be responsible for the design, implementation, and operation of the data lake and lakehouse architecture, with strong ownership of technical and architectural decisions. This includes designing and building reliable data pipelines, working with large-scale business and transactional data, and defining how data is stored, partitioned, processed, and monitored. You will work closely with Data Engineering, DevOps, Data Science, and other stakeholders to ensure data is accurate, reliable, and available for different use cases. You will also contribute to the data migration, drive data quality and pipeline reliability, and help shape the long-term scalability, performance, and maintainability of the data infrastructure.

Key Responsibilities:

Design, build, and maintain a multi-layer lakehouse (bronze/silver/gold) using open table formats such as Iceberg and Delta, including schema evolution and data organization

Design and build reliable CDC and streaming ingestion pipelines using Kafka, Debezium, or similar technologies, including handling late and duplicate events

Define and optimize data layouts in cloud object storage through partitioning, compaction, file sizing, and query performance optimization

Define and maintain data retention, archival, immutability, and GDPR-style deletion processes

Ensure data freshness, quality, and consistency, identify data drift, and drive reconciliation with source transactional systems

Define and implement data governance practices, including metadata, lineage, access controls, PII protection, encryption, and audit trails

Ensure pipeline and ingestion reliability, establish effective monitoring, and drive investigation and resolution of data anomalies

Collaborate with Data Engineering, DevOps, Data Science, Analytics, Finance, and Compliance teams on data requirements, migration, architecture, and long-term technical decisions

Required Competence and Skills:

5+ years of data engineering experience working with large-scale data systems, data lakes, or lakehouse environments

Strong production experience with cloud object storage (AWS S3 or equivalent) and at least one analytics platform such as Snowflake, Databricks, or BigQuery

Strong hands-on experience with open table formats such as Iceberg, Delta, or Hudi, including schema evolution and data organization

Strong understanding of partitioning, file layout, data storage, and query optimization for large datasets

Experience designing and building CDC and streaming data pipelines using Kafka, Debezium, or similar technologies

Strong SQL and data modeling skills, with solid knowledge of relational databases and transactional data

Experience with data quality, monitoring, and governance practices, including metadata, lineage, access control, PII handling, and retention

Hands-on experience with Python for data engineering tasks and experience with workflow orchestration tools such as Airflow or Dagster

Ability to take ownership of technical decisions, contribute to architecture and system design, and clearly explain technical choices and trade-offs

Nice to Have:

Experience working with financial, transactional, or ledger data

Experience in regulated or audit-heavy environments such as fintech, gaming, banking, payments, or similar industries

Experience participating in large-scale data migration projects

Why Us:

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

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