Data Engineer

Details of the offer

Job Title: Data Engineer
Position Overview
Our client is seeking a skilled and motivated Data Engineer to join their team.
The ideal candidate will be passionate about working with large datasets, optimizing data pipelines, and building scalable data systems that support business intelligence and analytics.
In this role, you will be instrumental in ensuring the integrity, availability, and scalability of the company's data infrastructure, enabling data-driven decision-making across the organization.
This is a fantastic opportunity to work with a forward-thinking team and solve complex data challenges, while contributing to the growth of their data capabilities.
Key Responsibilities Design & Build Data Pipelines: Develop, implement, and optimize ETL (Extract, Transform, Load) processes to integrate data from multiple sources into centralized repositories, ensuring data is clean, reliable, and accessible.Data Architecture & Management: Design and maintain scalable data architecture, ensuring efficient storage, retrieval, and management of structured and unstructured data.Database Optimization: Optimize and maintain SQL and NoSQL databases, focusing on schema design, query optimization, and ensuring data consistency and availability.Cloud Data Solutions: Build and deploy data solutions on cloud platforms (AWS, Azure, Google Cloud), using services like S3, Redshift, BigQuery, Snowflake, or similar technologies.Data Quality & Monitoring: Implement monitoring and alerting systems to ensure high data quality, availability, and timely processing.Collaboration: Work closely with data scientists, analysts, and stakeholders to understand data needs and ensure reliable, accessible data for decision-making.Automation & Optimization: Automate tasks and optimize existing workflows to improve performance, scalability, and efficiency.Documentation & Best Practices: Maintain clear documentation of data processes, workflows, and system architectures, adhering to best practices for data governance, security, and compliance.Required Skills & Qualifications Experience: 3+ years in data engineering, data pipeline development, or a related field.Technical Skills:Proficiency in Python, Java, Scala, or SQL.Experience with ETL tools (e.g., Apache Airflow, Talend, Fivetran).Hands-on experience with cloud platforms (AWS, Azure, Google Cloud) and services like Redshift, BigQuery, Snowflake, and S3.Familiarity with both SQL and NoSQL databases (e.g., MongoDB, Cassandra, PostgreSQL).Experience with Data Warehousing concepts and dimensional modeling (OLAP).Data Governance & Security: Understanding of best practices in data governance, security, and compliance (GDPR, HIPAA).Problem-Solving: Strong troubleshooting skills with the ability to resolve complex data issues.Collaboration & Communication: Ability to work with cross-functional teams and translate business requirements into technical solutions.Preferred Qualifications Cloud Certifications: AWS Certified Big Data – Specialty, Microsoft Azure Data Engineer Associate, or Google Cloud Professional Data Engineer.Containerization & DevOps: Familiarity with CI/CD pipelines.Data Visualization: Experience with tools like Tableau, Power BI, or Looker.Big Data Technologies: Knowledge of Hadoop, Spark, is a plus.Advanced Data Modeling: Experience with snowflake, and data lake design.What Our Client Offers Competitive Salary: Based on experience and qualifications.Career Growth: Opportunities for professional development, training, and certifications.Flexible Work Environment: Remote work options and flexible hours.Collaborative Culture: Work in a dynamic, supportive environment where innovation is encouraged and valued. #J-18808-Ljbffr


Nominal Salary: To be agreed

Source: Talent_Dynamic-Ppc

Requirements

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