The company is looking for a Data Engineer to build and maintain the data architecture that supports business needs, enabling analysts and data scientists to work with clean, accessible datasets by developing scalable data pipelines and managing data systems.
Requirements
- Strong proficiency in programming languages such as Python, Java, or Scala, with expertise in data processing frameworks and libraries (e.g., Spark, Hadoop, SQL, etc.)
- In-depth knowledge of database systems (relational and NoSQL), data modeling, and data warehousing concepts
- Experience with cloud-based data platforms and services (e.g., AWS, Azure, Google Cloud) including familiarity with relevant tools and technologies (e.g., S3, Redshift, BigQuery, etc.)
- Proficiency in designing and implementing ETL processes and data integration workflows using tools like Apache Airflow, Informatica, or Talend
- Familiarity with data governance practices, data quality frameworks, and data security principles
- A firm understanding of the SDLC process
- An understanding of object-oriented programming
Responsibilities
- building and maintaining the data architecture that supports our business needs
- developing scalable data pipelines to transform and move data from diverse sources
- designing, testing, and maintaining data architectures such as databases, data warehouses, data lakes, and large-scale processing systems
- assemble large, complex datasets to meet both functional and non-functional requirements
- build high-performance algorithms, predictive models, and proofs of concept
- using modern programming languages and tools to integrate systems and manage complex data workflows
- building and delivering high quality data architectures and pipelines that support clients, business analysts, and data scientists
Other
- 4-7 years experience working as a Data Engineer, preferably in a professional services or consulting environment
- Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions
- Excellent communication and collaborations skills, with the ability to effectively work with clients and cross-functional teams
- Self-motivated and proactive, with a passion for learning and staying updated with the latest trends and advancements in the field of data engineering
- Able to work with ambiguity and turn client wants and needs into working stories, epics which can be executed upon during a sprint.
