Who we are
We are a boutique management consulting firm offering Business Consulting, Advisory, and Technology services to our banking clients in the wealth space. We partner with our clients on large transformation projects and act as their delivery partners.
We are building a competency center with a high-potential team with niche skill sets. Our focus is to bring together, a diverse talent pool that will create perfect synergy in delivering the best possible solutions for the projects we undertake. We also aspire to provide an inclusive workplace where fresh talent can grow and achieve their full potential.
Job Description
The candidate must have 5+ years of experience in a Data Engineer role with a degree in Computer Science, Informatics, Information systems or similar fields.
Key responsibilities include:
· Designing and building scalable data pipelines to extract, transform, and load data from a variety of sources.
· Maintaining and optimizing existing data pipelines and automating data workflows such as data ingestion, aggregation, and ETL processing.
· Working with data analysts in Fintech space to understand data needs and design appropriate data models.
· Collaborating with cross-functional teams to integrate data pipelines with other systems.
· Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures.
· Monitor data systems performance and implement optimization strategies.
Minimum Qualifications:
· Strong development experience in at least two or more of the following languages: Python, Java, Scala, Go.
· Experience with working on large data sets and distributed computing in Enterprise using technologies like Hadoop, Spark, Hive, Kafka, etc.
· Proficient with building data pipelines and workflow management tools. Should have worked on Airflow, Nifi or related tools.
· Working knowledge of message queuing, stream processing systems like Kafka, Spark Streaming.
· Hands on experience working with NoSQL databases (like Cassandra, MongoDB, or Neo4j) and relational databases (like MySQL, PostgreSQL, or Oracle)
· Experience with data visualization tools like Tableau, Superset, or similar tools.
· Working knowledge of data quality, data governance, and data security principles.
Good to have:
· Experience with data science and machine learning tools and libraries (e.g. scikit-learn, TensorFlow, PyTorch, etc.)
· Cloud computing experience (e.g. AWS, GCP, Azure)
· Cloudera Certified Professional Data Engineer, IBM Certified Data Engineer, or similar certifications.
· Must be aware of data privacy and security concerns and regulations (e.g. GDPR, CCPA, etc.)
