Data Engineer

As an Enterprise Data Engineer, you’ll be instrumental in the development and maintenance of Data pipelines for the Finance Function of GoTo that supports Accounting, Planning and Taxation functions to automate various processes and providing data required for finance reporting. 

What You Will Do

• Design end-to-end scalable data infrastructure, including Data Warehouse (DWH) and analytics architecture.
• Build and maintain integrated data pipelines that support complex business and financial operations.
• Develop high-quality code and scripts using SQL and Python for data processing and automation.
• Create and optimize data solutions such as databases, dashboards, and analytics tools to meet evolving business needs.
• Conduct system and integration testing, ensuring compliance with organizational standards for metadata and access protocols.
• Implement robust data quality checks and monitoring systems for efficient data collection, storage, and retrieval.
• Collaborate with Engineering and cross-functional teams to align on data architecture, governance, and best practices.
• Analyze complex datasets to uncover insights, resolve issues, and support data-driven decision-making across domains.
• Drive innovation by contributing to open-source projects and advancing internal data tools and practices.

What You Will Need

• 2+ years of experience as a Data Engineer with a degree in Computer Science, Statistics, Informatics, or a related field.
• Strong knowledge of big data stacks and tools, including:
• -- Big Data DBs: MaxCompute (AliCloud), BigQuery (GCP), Azure (MS)
• -- Distributed systems: Spark, Hadoop, Presto, Hive
• -- Message queueing: Kafka, NSQL
• -- Databases: PostgreSQL, MySQL, Cassandra
• -- Data pipeline tools: Airflow
• -- Languages: Python, Java, C++, Scala
• Proficient in SQL, data programming, and building relational database queries.
• Deep understanding of data architecture, database structures, warehousing, and data mining concepts.
• Skilled in designing, building, and optimizing scalable data pipelines and infrastructure.
• Experience with cloud platforms (GCP preferred) and UNIX environments.
• Ability to implement robust data quality checks, monitoring, and automation processes.
• Strong analytical skills for investigating issues and identifying patterns in complex data sets.
• Excellent communication and teamwork skills in cross-functional and international settings.