Senior Data Engineer

Company Overview: Sundew is a leading digital transformation firm with an 18-year legacy of excellence. We specialize in digital strategy, application development, and engineering, utilizing MEAN, MERN, and LAMP stacks, with PHP Laravel as our primary proficiency. We are looking for a Senior Data Engineer who will take ownership of end-to-end data strategy, mentor and guide a team, and ensure seamless delivery of high-quality data pipelines, storage solutions, and analytics platforms. About the Role: This role requires strong expertise in data engineering technologies, ETL development, data architecture design, Agile methodologies, and root cause analysis, along with exposure to emerging trends such as AI-driven data processing and advanced analytics. Roles and Responsibilities: Data Pipeline Development: Design, develop, and maintain scalable data pipelines to support ETL (Extract, Transform, Load) processes using tools like Apache Airflow, AWS Glue, or similar. Database Management: Design, optimize, and manage relational and NoSQL databases (such as MySQL, PostgreSQL, MongoDB, or Cassandra) to ensure high performance and scalability. SQL Development: Write advanced SQL queries, stored procedures, and functions to extract, transform, and analyze large datasets efficiently. Cloud Integration: Implement and manage data solutions on cloud platforms such as AWS, Azure, or Google Cloud, utilizing services like Redshift, BigQuery, or Snowflake. Data Warehousing: Contribute to the design and maintenance of data warehouses and data lakes to support analytics and BI requirements. Programming and Automation: Develop scripts and applications in Python or other programming languages to automate data processing tasks. Data Governance: Implement data quality checks, monitoring, and governance policies to ensure data accuracy, consistency, and security. Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand data needs and translate them into technical solutions. Performance Optimization: Identify and resolve performance bottlenecks in data systems and optimize data storage and retrieval. Documentation: Maintain comprehensive documentation for data processes, pipelines, and infrastructure. Stay Current: Keep up-to-date with the latest trends and advancements in data engineering, big data technologies, and cloud services. Required Skills and Qualifications: 4+ years of experience in Data Engineering (or equivalent). Proficiency in SQL and relational databases (PostgreSQL, MySQL, etc.). Experience with NoSQL databases (MongoDB, Cassandra, etc.). Strong programming skills in Python; familiarity with Java or Scala is a plus. Experience with data pipeline tools (Apache Airflow, Luigi, or similar). Expertise in cloud platforms (AWS, Azure, or Google Cloud) and data services (Redshift, BigQuery, Snowflake). Knowledge of big data tools like Apache Spark, Hadoop, or Kafka is a plus. Data Modelling : Experience in designing and maintaining data models for relational and non-relational databases. Analytical Skills : Strong analytical and problem-solving abilities with a focus on performance optimisation and scalability. Soft Skills: Excellent verbal and written communication skills to convey technical concepts to non-technical stakeholders. Ability to work collaboratively in cross-functional teams. Certifications (Preferred): AWS Certified Data Engineer, GCP Professional Data Engineer, or similar. Mindset: Eagerness to learn new technologies and adapt quickly in a fast-paced environment.