Senior Data Engineer
to $9000
Product
We are looking for a Senior Data Engineer to join our growing team. In this role, you will help build and scale modern data infrastructure and pipelines that power analytics, business intelligence, product insights, and operational decision-making across our omni-channel commerce platform.
Responsibilities
- Design, build, and maintain scalable, reliable data pipelines and infrastructure across cloud environments.
- Develop and manage ETL/ELT workflows to ingest, transform, and load data from multiple sources into data warehouses and data lakes.
- Partner closely with product, engineering, analytics, and business teams to ensure trusted, accessible, and timely data across the organization.
- Optimize data storage, modeling, and query performance to support reporting, analytics, and operational use cases.
- Build and maintain batch and real-time data processing systems using modern tools and frameworks.
- Improve data reliability and quality by implementing monitoring, validation, alerting, and observability practices.
- Support deployment, scalability, and orchestration of data workloads using containerization and workflow automation tools.
- Implement and maintain CI/CD pipelines for data workflows and infrastructure.
- Ensure data governance, privacy, and security standards are upheld across all data systems.
- Contribute to architecture decisions, code reviews, documentation, and best practices for data engineering.
- Stay current with emerging technologies and best practices in data engineering to continuously improve platform capabilities.
Requirements
- Excellent communication skills, including fluent verbal English, with the ability to explain technical concepts to non-technical stakeholders and collaborate effectively across teams.
- Proven experience as a Data Engineer, with strong hands-on experience building and managing production-grade data pipelines.
- Strong proficiency with cloud platforms such as AWS and/or Azure, including modern data services.
- Experience with Python and strong SQL skills for data transformation, automation, and analysis.
- Experience with distributed data processing and streaming technologies such as Apache Spark, Kafka, or similar tools.
- Familiarity with workflow orchestration tools such as Airflow, DBT, or equivalent.
- Experience with data warehousing and lakehouse technologies such as Snowflake, Redshift, BigQuery, Databricks, or similar platforms.
- Solid understanding of ETL/ELT design patterns, data modeling, and data architecture best practices.
- Experience with Docker, Kubernetes, or other containerization and orchestration technologies.
- Familiarity with relational and NoSQL databases such as PostgreSQL, MongoDB, or Cassandra.
- Experience with version control systems such as Git.
- Strong problem-solving skills and a proactive approach to performance optimization, troubleshooting, and continuous improvement.
Preferred Qualifications
- Experience with data governance, security, and privacy best practices in cloud environments.
- Familiarity with infrastructure-as-code tools such as Terraform or CloudFormation.
- Experience supporting analytics, machine learning, or reporting use cases with well-structured data systems.
- Knowledge of BI and visualization tools such as Power BI or Tableau.
- Previous experience working in agile, cross-functional product and engineering teams.
- Experience in retail, e-commerce, omni-channel commerce, or POS platforms is a strong plus.
Why PredictSpring?
- Join a category-leading company transforming the future of retail and omni-channel commerce.
- Work with innovative technology powering seamless online and in-store customer experiences.
- Collaborate with a talented, global team in a flexible remote work environment.
- Enjoy opportunities for professional growth and career development.
- Make a direct impact on products used by some of the world’s most recognized retail brands.
- Be part of a fast-moving, collaborative, and customer-focused culture at the forefront of commerce innovation.
Required languages
| English | C1 - Advanced |
Published 24 April
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