The Role
Design, develop, and maintain data infrastructure, pipelines, ETL/ELT processes, data warehouses, models, and schemas. Transform and validate complex datasets, implement analytics solutions, and support data governance and quality. Collaborate with technical and non-technical stakeholders to translate business requirements into reliable data solutions. Document data processes and communicate findings across departments including Credit, Structuring, Operations, and Legal.
Summary Generated by Built In
As an Data Engineer, you will be responsible for designing, developing, and maintaining data infrastructure and analytics solutions to support data-driven decision-making and reporting. You will collaborate with other internal teams such as Business Intelligence, Data Operations, IT, and other stakeholders to understand business requirements and translate them into technical solutions. Your role will potentially involve working with large and complex data sets, implementing data pipelines, and ensuring data accuracy, integrity, and availability.
Responsibilities:
- Develop and maintain data infrastructure: Design, build, and optimize data pipelines, ETL/ELT processes, and data warehouses to support efficient data collection, storage, and retrieval.
- Data modeling and schema design: Define data models and schemas to enable efficient data analysis, reporting, and visualization. Ensure adherence to data governance and data quality standards.
- Data transformation and manipulation: Cleanse, transform, and aggregate data to derive meaningful insights. Identify data inconsistencies, outliers, and anomalies and implement appropriate solutions.
- Implement data analytics solutions: Collaborate with different company departments to understand their requirements and develop analytics solutions that meet their needs.
- Documentation and communication: Document data processes, data flows, and data structures. Clearly communicate technical concepts and findings to non-technical stakeholders such as Credit/Structuring, Operations, Legal, etc.
Requirements
Qualifications:
- Bachelor's degree in Computer Science, Information Systems, Data Science/Analytics, or a related field.
- 4+ years of experience as an Data Engineer, Analytical Engineer, Data Analyst, Business Intelligence Engineer, or similar role
- Experience working with finance-related data sets (ex: FinTech, Lending, Financial Services, or related industries)
- Advanced SQL skills and experience working with complex data sets.
- Understanding of the following is advantageous:
o Data Modeling
o Data Governance
o ETL/ELT practices
o Data transformations with dbt
o Data warehousing with Snowflake
o Cloud computing with AWS
o Data orchestration tools (e.g. Airflow, Dagster)
o API Usage and Integration - Strong analytical and problem-solving skills, with the ability to transform complex data into actionable insights.
- Excellent communication and collaboration skills, with the ability to interact effectively with both technical and non-technical stakeholders.
- Strong attention to detail and a commitment to delivering high-quality work within deadlines.
- Willingness to stay updated with emerging technologies, tools, and best practices in data engineering and analytics. Ability to adapt to evolving business needs and work in a fast-paced environment.
Skills Required
- Bachelor's degree in Computer Science, Information Systems, Data Science or Analytics, or a related field
- 4+ years of experience as a Data Engineer, Analytical Engineer, Data Analyst, Business Intelligence Engineer, or similar role
- Experience working with finance-related datasets, such as FinTech, lending, or financial services data
- Advanced SQL skills and experience working with complex datasets
- Strong analytical and problem-solving skills
- Excellent communication and collaboration skills with technical and non-technical stakeholders
- Strong attention to detail and commitment to high-quality work and deadlines
- Willingness to stay current with emerging technologies and adapt to evolving business needs
- Understanding of data modeling and data governance
- Understanding of ETL/ELT practices
- Experience with dbt for data transformations
- Experience with Snowflake for data warehousing
- Experience with AWS cloud computing
- Experience with data orchestration tools such as Airflow or Dagster
- Experience with API usage and integration
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The Company
What We Do
Fortunize is a Hyderabad-based consulting and technology services company that helps organizations become more agile and competitive. It partners with clients on strategy, marketing, operations, IT, digital transformation, methodology, advanced analytics, and sustainability. Its offerings include software and mobile app development, machine learning and AI, big data analytics, IT infrastructure management, and IT consulting, serving businesses across industries.
