Data Engineer
The company is looking for a skilled Data Engineer to design, build, and maintain the infrastructure that supports data management, processing, and analytics capabilities. In this role, you will work closely with cross-functional teams to develop scalable data pipelines, modern storage solutions, and effective data governance frameworks.
You will play a key role in ensuring that organisational data is accurate, accessible, secure, and optimised for reporting, analytics, and machine learning use cases.
- Design, develop, and maintain scalable and efficient data pipelines for collecting, processing, transforming, and storing large volumes of data.
- Build, manage, and optimise modern data storage solutions, including data lakes and data warehouses.
- Collaborate with cross-functional teams to define and implement data governance, security, and compliance practices.
- Partner with data analysts and data scientists to optimise data architecture for reporting, analytics, and machine learning workloads.
- Monitor data pipelines and storage infrastructure, identify performance or reliability issues, and implement appropriate solutions.
- Ensure data quality, accuracy, consistency, and integrity through validation, monitoring, and control mechanisms.
- Conduct code reviews and contribute to the continuous improvement of engineering standards and practices.
- Mentor and support junior engineers when required.
- Communicate with business stakeholders to understand data requirements and deliver effective, scalable solutions.
- Stay up to date with emerging technologies, industry trends, and best practices in data engineering.
- Bachelor’s degree in Computer Science, Information Systems, Software Engineering, or a related field. (required)
- At least 3 years of hands-on experience in data engineering or a related technical role. (required)
- Strong expertise in SQL, database design, and data modeling. (required)
- Proficiency in at least one programming language, such as Python, Java, or Scala. (required)
- Strong knowledge of ETL and ELT processes, tools, and best practices. (required)
- Experience working with relational and NoSQL databases. (required)
- Experience with Linux-based environments and Bash scripting. (required)
- Hands-on experience with data warehouse technologies such as Snowflake, Amazon Redshift, or Google BigQuery. (required)
- Knowledge of Big Data technologies, including Hadoop and Apache Spark. (required)
- Experience with data streaming technologies such as Apache Kafka and Spark Streaming. (required)
- Experience with workflow orchestration tools such as Apache Airflow, AWS Glue, or similar platforms. (required)
- Practical experience with cloud-based data platforms, including AWS, Microsoft Azure, or Google Cloud Platform. (required)
- Experience implementing CI/CD pipelines for data workflows. (required)
- Familiarity with version control systems, particularly Git. (required)
- Knowledge of data security, privacy, and regulatory compliance standards, including GDPR and HIPAA. (required)
- Exposure to data cataloging, metadata management, and data lineage tools such as Apache Atlas or Amundsen. (required)
- Strong analytical and problem-solving skills. (required)
- Excellent communication and collaboration abilities. (required)
- High attention to detail and the ability to perform effectively in a fast-paced environment. (required)
Digitain is a business-to-business provider of sportsbook and iGaming platform software, headquartered in Yerevan, Armenia. Founded in 1999, it offers a turnkey and standalone platform spanning sports betting, online and live casino, and games, alongside managed services for operators across regulated and emerging markets. Its portfolio includes the Imagine Live live-casino studios and the Galaxsys games studio, and the group employs a large engineering and operations workforce.