Data Engineer

We are looking for a Mid-Level Data Engineer to join our team in BGC. In this role, you will collaborate with cross-functional teams to design, build, and maintain robust data pipelines and data solutions. You will work closely with business and IT stakeholders to transform raw data into actionable insights using modern cloud technologies and data warehousing standards.

Key Responsibilities:

• Analyze internally and externally sourced raw data to generate BI and advanced analytics datasets based on stakeholder requirements.
• Design and implement efficient data pipelines to curate sourced data into the in-house data warehouse.
• Develop data marts to facilitate dataset consumption from the in-house data warehouse by business and IT stakeholders.
• Implement data model changes in alignment with in-house data warehouse standards.
• Assist in planning and executing migration activities to transition data from existing database solutions to the in-house data warehouse.
• Perform regular housekeeping and optimization of raw data and datasets stored in the in-house data warehouse.
• Build, test, and maintain resilient data pipelines and data platforms.
• Develop data solution prototypes to support evolving business needs.
• Explore and implement methods to enhance data quality, consistency, and reliability.
• Identify opportunities to acquire higher-quality raw data sources.
• Develop and maintain analytical tools to support BI and advanced analytics activities.
• Execute end-to-end data migrations from legacy databases to the modern in-house data warehouse.
• Adhere to and promote data engineering standards and best practices within the team.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related quantitative discipline.
• 3 to 5 years of hands-on experience in data engineering or a similar role (experience in the financial industry is a plus).
• Solid understanding or practical experience working within Enterprise Agile frameworks (e.g., Scrum, Kanban, SAFe).
• Solid understanding of ETL/ELT processes, data warehousing concepts, BI tools (e.g., Qlik), and advanced data analytics concepts.
• Knowledge of cloud-enabled technologies such as AWS (AWS Glue, AWS RDS, AWS Fargate, etc.).
• Practical experience with databases and cloud data warehouses, specifically Snowflake, PostgreSQL, and MS SQL.
• Strong programming skills with solid knowledge of Python and/or Java.

Certifications (Preferred / Advantageous):

• AWS Certified Data Engineer – Associate / Specialty or AWS Certified Solutions Architect – Associate
• Snowflake SnowPro Core Certification

Soft Skills:

• Excellent critical thinking, analytical, and problem-solving skills.
• Strong communication skills with a collaborative, team-oriented mindset.