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Job Description for Senior Data Engineer
 

Objectives and Purpose

The Senior Data Engineer ingests, builds, and supports large-scale data architectures that serve multiple downstream systems and business users. This individual supports the Data Engineer Leads and partners with Visualization on data quality and troubleshooting needs. The Senior Data Engineer will: Clean, aggregate, and organize data from disparate sources and transfer it to data warehouses. Support development testing and maintenance of data pipelines and platforms, to enable data quality to be utilized within business dashboards and tools. Create, maintain, and support the data platform and infrastructure that enables the analytics front-end; this includes the testing, maintenance, construction, and development of architectures such as high-volume, large-scale data processing and databases with proper verification and validation processes.

 

Your key responsibilities

Develop and maintain scalable data pipelines, in line with ETL principles, and build out new integrations, using AWS native technologies, to support continuing increases in data source, volume, and complexity. Define data requirements, gather, and mine data, while validating the efficiency of data tools in the Big Data Environment. Lead the evaluation, implementation and deployment of emerging tools and processes to improve productivity. Implement processes and systems to provide accurate and available data to key stakeholders, downstream systems, and business processes. Partner with Business Analysts and Solution Architects to develop technical architectures for strategic enterprise projects and initiatives. Coordinate with Data Scientists to understand data requirements, and design solutions that enable advanced analytics, machine learning, and predictive modelling. Mentor and coach junior Data Engineers on data standards and practices, promoting the values of learning and growth. Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.

 

To qualify for the role, you must have the following:

Essential skillsets

Bachelor's degree in engineering, Computer Science, Data Science, or related field 5-9 years of experience in software development, data science, data engineering, ETL, and analytics reporting development Experience in building and maintaining data and system integrations using dimensional data modelling and optimized ETL pipelines. Experience in design and developing ETL pipelines using ETL tools like IICS, Datastage, Abinitio, Talend etc. Proven track record of designing and implementing complex data solutions Demonstrated understanding and experience using: Data Engineering Programming Languages (i.e., Python, SQL) Distributed Data Framework (e.g., Spark) Cloud platform services (AWS preferred) Relational Databases DevOps and continuous integration  AWS knowledge on services like Lambda, DMS, Step Functions, S3, Event Bridge, Cloud Watch, Aurora RDS or related AWS ETL services Knowledge of Data lakes, Data warehouses Databricks/Delta Lakehouse architecture Code management platforms like Github/ Gitlab/ etc., Understanding of database architecture, Data modelling concepts and administration. Handson experience of Spark Structured Streaming for building real-time ETL pipelines. Utilizes the principles of continuous integration and delivery to automate the deployment of code changes to elevate environments, fostering enhanced code quality, test coverage, and automation of resilient test cases. Proficient in programming languages (e.g., SQL, Python, Pyspark) to design, develop, maintain, and optimize data architecture/pipelines that fit business goals. Strong organizational skills with the ability to work multiple projects simultaneously and operate as a leading member across globally distributed teams to deliver high-quality services and solutions. Excellent written and verbal communication skills, including storytelling and interacting effectively with multifunctional teams and other strategic partners Strong problem solving and troubleshooting skills Ability to work in a fast-paced environment and adapt to changing business priorities

Desired skillsets

Master's degree in engineering specialized in Computer Science, Data Science, or related field Demonstrated understanding and experience using: Knowledge in CDK Experience in IICS Data Integration tool Job orchestration tools like Tidal/Airflow/ or similar   Knowledge on No SQL Proficiency in leveraging the Databricks Unity Catalog for effective data governance and implementing robust access control mechanisms is highly advantageous. Databricks Certified Data Engineer Associate AWS Certified Data Engineer - Associate

 

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