The company is seeking a skilled and experienced Data Engineer to join their data team.
The Data Engineer will be responsible for designing, building, and maintaining scalable and efficient data pipelines and architectures that support various data-driven initiatives.
The role involves developing, constructing, testing, and maintaining scalable data pipelines for ingestion, processing, and storage of large data sets from multiple sources.
The Data Engineer will optimize data architectures for both structured and unstructured data to support batch and real-time data processing.
Responsibilities include integrating data from different source systems into the data lake or data warehouse and implementing and managing ETL processes for efficient data movement, cleaning, and transformation.
The Data Engineer will ensure data quality, consistency, and integrity through proper validation and testing.
The role requires designing and implementing database solutions that support data storage, transformation, and querying, as well as building and maintaining data warehouse solutions for business intelligence and analytics needs.
The Data Engineer will work with cloud platforms such as AWS, Azure, or Google Cloud to implement data storage, processing, and streaming architectures.
Collaboration with data scientists, analysts, software engineers, and business teams is essential to understand data requirements and deliver solutions that meet their needs.
The Data Engineer will implement data governance standards, data security, and compliance measures to protect sensitive data and ensure compliance with data privacy regulations.
Performance monitoring and optimization of data pipelines is a key responsibility, along with automating repetitive tasks and developing tools for data access, management, and analysis.
Requirements:
A Bachelor’s degree in Computer Science, Engineering, or a related field is required.
Proven experience as a Data Engineer, Software Engineer, or similar role in large scale data platform implementation is essential.
Strong experience in SQL and relational database systems such as MySQL, PostgreSQL, or Oracle is required.
Proficiency in programming languages such as Python, Java, or Scala for data manipulation and ETL tasks is necessary.
A minimum of 5 years of hands-on experience with ETL tools like Apache Nifi, Talend, Informatica, or equivalent is required.
Familiarity with big data technologies such as Hadoop, Spark, Kafka, and HBase is essential.
A minimum of 3 years of hands-on experience with cloud-based data services like AWS S3, Azure Data Lake, Google BigQuery, or Redshift is required.
Knowledge of data modelling, database design, and data architecture best practices is necessary.
Experience with version control systems like Git and agile development practices is required.
Preferred skills include experience with NoSQL databases, Databricks, Dataiku, machine learning pipelines, CI/CD pipelines, and real-time data processing tools.
Understanding of data privacy regulations and their impact on data storage and processing is preferred.
Personal attributes should include strong problem-solving skills, excellent communication skills, attention to detail, and a proactive mindset.
Benefits:
The company offers industry-leading compensation and benefits.
Employees have access to top training and development opportunities to grow their careers and achieve personal ambitions.
The organization promotes an inclusive and entrepreneurial culture.
Employees can work in a dynamic environment with opportunities to collaborate with expert colleagues.
The company has been recognized for its exceptional standards in employee conditions and is listed among the top employers in various regions.
Employees are encouraged to apply even if they do not meet all the requirements, fostering a culture of learning and impact.
