Data Engineer

Company Description D2N Solutions is a talent and solutions provider focused on helping organizations build strong, domain-expert teams that align with their culture and business goals. The company's multidisciplinary team includes recruitment, compliance, finance, and marketing professionals who understand the challenges faced by both clients and candidates in a dynamic employment market. D2N Solutions offers comprehensive support and staffing services across Information Technology, Technology Infrastructure, and Business Consulting. Their IT services span areas such as artificial intelligence, information security, big data, business intelligence, cloud computing, and ERP, while infrastructure offerings include data centers, networks, DBA services, and security services. They also serve multiple industry verticals, including banking, financial services, ecommerce, healthcare, manufacturing, telecom, and government.
Role Description The Data Engineer role at D2N Solutions is a full-time remote position focused on building and maintaining scalable data solutions that support analytics, reporting, and business operations. Day-to-day responsibilities include designing and implementing data pipelines, integrating data from multiple sources, and developing robust ETL processes to ensure data quality, consistency, and reliability. The Data Engineer will collaborate with data analysts, data scientists, and business stakeholders to define data requirements, optimize data models, and improve overall data architecture. The role also involves maintaining data warehouses and data lakes, monitoring performance, troubleshooting data issues, and adhering to best practices in security, compliance, and documentation. This position offers the opportunity to contribute to data-driven initiatives across a wide range of industries and technology domains.
Qualifications

• Strong proficiency in Data Engineering, including building and maintaining data pipelines and working with large-scale data systems.
• Experience with Data Modeling and Data Warehousing, including designing schemas and optimizing storage for analytics and reporting.
• Hands-on expertise in Extract Transform Load (ETL) processes, including development, orchestration, and performance tuning.
• Ability to apply Data Analytics skills to support reporting, dashboards, and insights for business and technical stakeholders.
• Proficiency in SQL and at least one programming language commonly used in data engineering (such as Python, Scala, or Java).
• Experience with cloud data platforms and tools (for example, AWS, Azure, GCP, Snowflake, Redshift