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.
