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Hybrid in Ecuador: Quito
Data Software Engineering& 6 others
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We are seeking a Data Software Engineer to design, develop, and optimize data products that support the bank's Data Architecture vision, ensuring robust, efficient, and well-documented solutions delivered within agreed timeframes.
Responsibilities
- Analyze requirements based on provided definitions and designs
- Participate in the solution engineering and design phase, ensuring high efficiency standards aligned with the Data Architecture vision
- Develop and deploy data products, such as ETLs, ELTs, and APIs, to make information accessible, adhering to established standards and development best practices
- Apply testing strategies to verify that functional and non-functional requirements are correctly implemented
- Implement continuous improvement processes for products under development
- Participate actively in pair programming to identify opportunities for improvement in colleagues' work
- Resolve incidents promptly and propose long-term solutions to prevent recurrence
- Manage the necessary enablers for development tasks, with support and supervision from the assigned Senior Data Engineer
- Document developed data products in accordance with the standards and platforms provided by the bank
Requirements
- 3 to 5 years of experience in database management and query, stored procedure, and script optimization
- Experience in modeling relational and non-relational databases, and in building data warehouses, data marts, and data lakes
- Familiarity with cloud technologies for Big Data solutions, including building ETL and ELT processes for large volumes of data
- Knowledge of development best practices such as Clean Code, and familiarity with Agile frameworks and DataOps strategies
- Skills in data-oriented testing strategies for functional and non-functional testing
- Background in distributed file systems such as Hadoop, HDFS, or Spark, and in batch processing using Big Data technologies
- Proficiency in relational database engines such as Oracle, SQL, or PostgreSQL, and in NoSQL databases such as MongoDB, Cassandra, Elasticsearch, or Neo4j
- Experience with ETL tools for on-premises environments such as SSIS, Pentaho (Kettle), or SAP Data Services, and with cloud pipeline tools such as Azure Data Factory, AWS Glue, or Dataflow
- Familiarity with key components of cloud platforms such as AWS, Google Cloud Platform, and Microsoft Azure
- Proficiency in Apache Spark (SQL and Python) and PySpark
- Experience with version control tools
- Strong soft skills, including goal orientation, critical thinking, teamwork, effective communication, accountability, and planning
- Ability to explain technical concepts to non-technical stakeholders and a proactive approach to resolving blockers
Nice to have
- AI certification at any level (e.g., Copilot)
- Familiarity with Claude, Gemini, GPT, or Grok
- Knowledge of the banking/financial sector