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.
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.
Similar Jobs
Information Technology
Support development, monitoring, and troubleshooting of ETL/ELT pipelines and data marts. Assist with data modeling, profiling, lineage, documentation, and incident resolution. Collaborate with business partners and senior engineers to implement data solutions, support data quality, and participate in cloud modernization and migration efforts.
Top Skills:
AirflowDb2DbtFivetranGitOracleOracle Data Integrator (Odi)Pl/SqlPythonSnowflakeSQL
Fintech • Information Technology • Software • Financial Services
Develop, enhance, and support ETL/data pipelines using Sparkola, PySpark and SQL. Build and manage batch and ad-hoc pipelines via Sparkola Job Server, use Cloudera Machine Learning for development, validate datasets for downstream analytics (QlikSense/Superset), engage stakeholders to translate requirements, support production issues, and follow JIRA-driven delivery and governance controls.
Top Skills:
Cloudera Machine Learning (Cml)JIRAExcelPysparkQliksenseSparkolaSparkola Job ServerSQLSuperset
Marketing Tech • Sales • Consulting
Lead the design and delivery of data-driven solutions for commercial strategy in life sciences, guiding cross-functional teams, developing data products, and providing mentorship.
Top Skills:
Ai ToolsCSSDatabricksFast ApiHTMLMySQLOraclePostgresPysparkPythonReact JsSnowflake
What you need to know about the Hyderabad Tech Scene
Because of its proximity to leading research institutions and a government committed to the city's growth, Hyderabad's tech scene is booming. With plans to establish India's first "AI city," the city is on track to become one of the world's most anticipated tech hubs, with companies like TransUnion, Schrödinger and Freshworks, among others, already calling the city home.
