Data Engineer

Role Overview

We are looking for a skilled and driven Data Engineer to architect, develop, and sustain robust, scalable, and efficient data platforms and pipelines. The successful applicant should have hands-on experience managing extensive data environments and working with contemporary cloud-centric data technologies. A strong emphasis on data quality, validation, cleansing, and governance is critical for this role.

This position calls for a proactive individual adept at working autonomously, collaborating closely with clients and stakeholders, and engaging in strategic projects. Adaptability to evolving technologies and enthusiasm for enhancing processes, standards, and operational methods are essential.

Key Responsibilities

• Create and maintain scalable data workflows and ETL/ELT systems.
• Optimize and build solutions that handle large-scale structured and unstructured data.
• Design modern data infrastructures supporting analytics, reporting, machine learning, and business intelligence.
• Ensure platforms' security, reliability, scalability, and maintainability.
• Manage both real-time and batch data processing needs.
• Develop and oversee data validation, cleansing, and quality assurance activities.
• Implement tools for monitoring, auditing, and alerting to uphold data integrity.
• Identify and fix data irregularities, inconsistencies, and performance issues.
• Establish robust data governance, lineage tracking, and metadata management practices.
• Develop and support platforms using Databricks, Snowflake, Azure Synapse Analytics, SQL Server, and PostgreSQL.
• Enhance database performance, query efficiency, and storage methods.
• Participate in data migration, modernization, and system integration projects.

Required Skills & Experience

• A minimum of 4 years designing, implementing, and maintaining complex data platforms and solutions.
• Bachelor’s degree in Computer Science, IT, Engineering, or a related field.
• Proficiency with Databricks, Snowflake, Azure Synapse Analytics, Microsoft SQL Server, and PostgreSQL.
• Expertise in SQL development and query optimization.
• Experience in developing ETL/ELT pipelines and integrating multiple data sources.
• Solid understanding of data modeling, data warehousing, and lakehouse architecture concepts.
• Skilled in implementing data quality assurance, validation, cleansing, and reconciliation procedures.
• Experience with cloud-based data platforms and modern data engineering methodologies.
• Familiarity with CI/CD pipelines, DevOps culture, automation, and infrastructure-as-code is advantageous.
• Ability to work with minimal oversight and drive client-centered business outcomes.
• Adaptable to changing technological environments and diverse technology stacks.
• Demonstrates a positive, collaborative, and solution-oriented mindset.