Data Engineering Lead

About Brownloop :

Brownloop is a US-based fintech company focused on leveraging data, analytics, and AI solutions to help Private Equity firms make smarter investment decisions. We work with some of the largest and most reputed Private Equity companies in the world. We plan to expand our presence into India by setting up our core data competency and product development center, extending and supporting our current team and customers based in the US.

Job Summary :

We are in search of a proficient Senior Data Engineer with minimum 10 years of experience to join our innovative team. The chosen candidate will lead the conceptualization, design, and deployment of our data solutions tailored to meet our clients' unique business requirements. This role involves significant collaboration with data scientists, architects, and other stakeholders to ensure the integrity and efficiency of data systems.

Apart from having strong technical skills, we are looking to onboard candidates who can drive independent conversations with business teams and manage engagements.

We are offering this position in India, fully remote with limited travel requirements.

Key Responsibilities :

• Data Analysis and Organization : Analyse and organize raw data to derive actionable insights.
• Data Systems and Pipelines : Build and maintain robust data systems and pipelines to ensure seamless data flow.
• Business Needs Assessment : Evaluate business needs and objectives to design appropriate data solutions.
• Trend Interpretation : Interpret trends and patterns to support business decision-making.
• Complex Data Analysis : Conduct complex data analyses and report on findings to stakeholders.
• Data Preparation : Prepare data for prescriptive and predictive modeling.
• Algorithm and Prototype Development : Build algorithms and prototypes to enhance data processing capabilities.
• Data Integration : Combine raw information from various sources to create comprehensive data sets.
• Data Quality Enhancement : Explore and implement ways to improve data quality and reliability.
• Data Acquisition Opportunities : Identify opportunities for new data acquisition to enhance analytics capabilities.
• Analytical Tool Development : Develop analytical tools and programs to support data-driven decision-making.
• Collaboration : Collaborate with data scientists and architects on multiple projects to ensure the success of data initiatives.

Requirements and Skills :

Experience :

Technical Skills :

Education :

a Master’s degree is a plus.