Sobre este puesto de Software Engineer I en Precisely International Jobs
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Precisely is the leader in data integrity. We empower businesses to make more confident decisions based on trusted data through a unique combination of software, data enrichment products and strategic services. What does this mean to you? For starters, it means joining a company focused on delivering outstanding innovation and support that helps customers increase revenue, lower costs and reduce risk. In fact, Precisely powers better decisions for more than 12,000 global organizations, including 95 of the Fortune 100. Precisely's 2500 employees are unified by four company core values that are central to who we are and how we operate: Openness, Determination, Individuality, and Collaboration. We are committed to career development for our employees and offer opportunities for growth, learning and building community. With a "work from anywhere" culture, we celebrate diversity in a distributed environment with a presence in 30 countries as well as 20 offices in over 5 continents. Learn more about why it's an exciting time to join Precisely!
Precisely is an AI-first organization. All employees are expected to demonstrate proficiency in applying AI tools to accelerate their work, improve output quality, and eliminate low-value tasks. Candidates should be comfortable using generative AI tools (e.g., Microsoft Copilot, ChatGPT) in their day-to-day workflows, able to evaluate AI-generated outputs critically, and open to continuously adopting new AI capabilities as they emerge.
Overview:
As a Software Engineer I, you will build and support scalable data pipelines, platform services, and analytics-ready datasets for Location Intelligence data products. You will work with engineering, product, QA, and data science teams to deliver reliable ingestion, transformation, validation, enrichment, and delivery capabilities using modern software engineering and AI-assisted development practices.
What you will do:
- Design, develop, test, and maintain data ingestion, transformation, validation, and delivery pipelines.
- Build scalable batch and distributed processing workflows using Python, Spark, SQL, and cloud data services.
- Develop reusable components, APIs, and platform utilities for data movement, quality checks, enrichment, and downstream consumption.
- Take ownership of assigned features from design through deployment, monitoring, and production support.
- Apply clean coding, unit testing, peer reviews, CI/CD, documentation, and operational readiness practices.
- Collaborate with cross-functional teams to convert business needs into maintainable technical solutions.
- Improve data quality, performance, lineage, accuracy, and completeness across assigned products and pipelines.
- Use GenAI, AI coding assistants, vibe coding, and software design-driven development practices to improve productivity, prototyping, testing, and solution quality.
What we are looking for:
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Engineering, Information Systems, or a related discipline (equivalent work experience will be considered in place of a degree).
- Relevant Experience: 1-3 years of experience in software engineering, data engineering, ETL/ELT development, data processing, or related engineering roles.
- Strong hands-on experience with Python and SQL.
- Good understanding of data engineering fundamentals, including data ingestion, transformation, validation, and data quality practices.
- Experience working with relational databases, data modeling concepts, query optimization, joins, aggregations, and data manipulation.
- Familiarity with Spark and distributed data processing concepts.
- Working knowledge of Git/GitHub, unit testing, debugging, code reviews, and agile software development practices.
- Ability to write clean, maintainable code and troubleshoot application or data pipeline issues with guidance from senior engineers.
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Strong problem-solving, analytical, and communication skills.
- Exposure to cloud platforms such as AWS (S3, Athena, EMR, EC2), GCP, Azure, Databricks, Snowflake, or Redshift.
- Exposure to large-scale data processing and analytics environments.
- Experience with AI-powered developer tools such as GitHub Copilot, ChatGPT, or similar coding assistants.
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