Senior Data Engineer

Established in 2008, Geidea epitomizes customer focused empowerment and commercial success through continuous innovation.

Geidea makes best in class digital payment solutions available for all by attracting and leveraging the best creative & entrepreneurial talent in the market

Our solutions give any business the chance to get ahead and reach for more no matter their size or maturity.

Our technology mirrors our people - Smart, Innovative & Forward Thinking

www.geidea.net

To maintain a competitive advantage as we grow, we are currently looking for a new Senior Data Engineer

.
Job purpose

: to maintain a competitive advantage as we grow, we are looking for a highly skilled Senior Data Engineer to design, develop, and optimize scalable, secure, and high-performance data platforms across the enterprise. This role will play a key part in building and maintaining the data ecosystem that supports our Fintech services, including real-time financial transactions, credit scoring models, regulatory reporting, and customer analytic

s.The Senior Data Engineer will work closely with Data Architects, Software Engineers, Product Teams, and Data Analysts to develop modern data solutions leveraging Big Data technologies, Data Lakes, ELT/ETL pipelines, and Cloud Data Warehouses while ensuring reliability, security, governance, and regulatory complianc

e.
Responsibiliti

es:Data Engineering & Platform Developm

• entDesign, build, and maintain scalable data pipelines for batch and real-time data processi
• ng.Develop and optimize data ingestion frameworks from internal and external data sourc
• es.Implement and maintain data models to support analytics, reporting, and operational use cas
• es.Collaborate with Data Architects to translate architectural designs into production-ready solutio

ns.Big Data & Distributed Process

• ingDevelop and maintain large-scale data processing solutions using technologies such as Apache Spark, Databricks, Flink, Trino, or Pres
• to.Build and optimize distributed data processing workloads handling high-volume financial and behavioral datase
• ts.Work with distributed storage systems including S3, ADLS, HDFS, and related cloud-native servic
• es.Optimize data formats such as Parquet, ORC, and Avro for performance and storage efficien

cy.Data Lakes & Lakehouse Soluti

• onsBuild and maintain Data Lake and Lakehouse environments using technologies such as Delta Lake, Apache Hudi, or Apache Icebe
• rg.Implement data quality, partitioning, schema evolution, and lifecycle management process
• es.Support data governance and metadata management initiatives across all data laye

rs.ELT/ETL Developm

• entDesign, develop, and support robust ELT/ETL pipelines using tools such as Apache Airflow, DBT, AWS Glue, Azure Data Factory, or Kafka Conne
• ct.Develop reusable and maintainable transformation logic using SQL, Python, or Sca
• la.Ensure pipeline reliability through monitoring, alerting, logging, and automated recovery mechanis
• ms.Optimize data processing performance and cost efficien

cy.Data Warehousing & Analytics Enablem

• entDevelop and maintain cloud-based data warehouse solutions such as Snowflake, Redshift, BigQuery, or Synapse Analyti
• cs.Build and optimize dimensional models, fact tables, and data marts to support business intelligence and reporting requiremen
• ts.Collaborate with analytics teams to ensure efficient access to trusted and governed data asse
• ts.Support integration with BI platforms such as Power BI, Tableau, and Look

er.Security, Governance & Complia

• nceImplement data security controls including encryption, masking, tokenization, and access manageme
• nt.Ensure compliance with SAMA, NCA, GDPR, and internal security polici
• es.Support data lineage, auditing, and governance initiatives through integration with metadata and cataloging solutio
• ns.Participate in data quality and governance programs to ensure accuracy and consistency of enterprise da

ta.DevOps & Observabil

• ityContribute to CI/CD pipelines and Infrastructure as Code implementations using Terraform, CloudFormation, or similar too
• ls.Implement monitoring and observability solutions for data pipelines and platfor
• ms.Establish and maintain SLAs, data quality checks, and operational dashboards using tools such as Grafana, Prometheus, or Datad
• og.Troubleshoot production issues and provide performance tuning recommendatio

ns.
Qualificati

• ons:Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related technical fi
• eld.5+ years of experience in Data Engineering, with hands-on experience building and supporting production-grade data platfo
• rms.Strong experience with Big Data technologies such as Apache Spark, Databricks, Flink, or similar distributed processing framewo
• rks.Proven experience building and maintaining Data Lakes, Lakehouse architectures, and cloud-based data platfo
• rms.Strong proficiency in SQL and at least one programming language such as Python, Scala, or J
• ava.Experience developing ELT/ETL pipelines using Airflow, DBT, AWS Glue, Azure Data Factory, or equivalent to
• ols.Hands-on experience with cloud platforms such as AWS, Azure, or
• GCP.Experience with cloud data warehouses including Snowflake, Redshift, BigQuery, or Syna
• pse.Understanding of data governance, security, and regulatory requirements within Fintech, Banking, or highly regulated environme
• nts.Experience working with CI/CD, Infrastructure as Code, and monitoring tools is highly prefer

red.
Our values guide how we think and act - They describe what we care about the

mostCustomer first - It's embedded in our design thinking and customer service app

roachOpen - Openness allows us to constantly improve and e

volveReal - No jargon and no exc

uses!Bold - Constantly challenging ourselves and our way of thin

king.Resilient – If we fail, we bounce back stronger than be

fore.Collaborative - We know that we can achieve a lot more as a

team.We are changing lives by constantly striving for a better solu