Data Engineer

Success Recruitments is seeking a Data Engineer to build and maintain scalable data infrastructure supporting analytics, reporting, machine learning, AI, and enterprise applications. The role focuses on developing cloud-based pipelines and platforms, integrating diverse data sources, improving data quality and reliability, and partnering with technical and business teams on modernization initiatives.

Responsibilities:

• Design, build, and maintain scalable data pipelines supporting analytics, reporting, machine learning, and enterprise applications
• Develop reliable batch and real-time data processing workflows across structured and unstructured data sources
• Build and optimize cloud-based data platforms, data warehouses, data lakes, and lakehouse architectures
• Develop reusable data models and transformation frameworks that improve consistency across business domains
• Integrate data from enterprise applications, APIs, databases, event streams, and third-party platforms
• Improve pipeline performance, scalability, reliability, and cost efficiency
• Implement automated data-quality checks, monitoring, lineage, and operational alerting
• Develop orchestration workflows and support CI/CD practices for data engineering
• Partner with Data Science, Analytics, AI/ML, Software Engineering, Product, and business teams to translate data requirements into production solutions
• Diagnose complex data and pipeline failures and implement permanent corrective solutions
• Support appropriate security, privacy, access-control, and data-governance standards
• Contribute to modernization of legacy data environments and migration toward cloud-native architecture
• Support enterprise cloud and data-platform modernization initiatives
• Help establish scalable data foundations for analytics, machine learning, and generative AI
• Contribute technical expertise to enterprise data architecture and platform roadmaps
• Improve data availability and quality across critical business functions
• Support migration from legacy ETL environments toward modern cloud-native data platforms
• Help establish reusable engineering standards that accelerate delivery across data teams
• Contribute to data-governance, security, and responsible AI initiatives

Requirements:

• • Bachelor's degree in Computer Science, Data Engineering, Software Engineering, Information Systems, or a related technical discipline, or equivalent practical experience
• • Strong proficiency in SQL and at least one programming language such as Python, Java, Scala, or Go
• • Experience developing ETL/ELT pipelines and complex data transformations
• • Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform
• • Working knowledge of modern data platforms such as Snowflake, Databricks, BigQuery, Redshift, Synapse , or comparable technologies
• • Familiarity with technologies such as Apache Spark, Kafka, Airflow, dbt , or equivalent data-processing and orchestration frameworks
• • Understanding of relational, dimensional, and modern analytical data-modeling principles
• • Knowledge of data warehousing, data lakes, and lakehouse architecture
• • Understanding of data security, governance, quality, and access-management principles
• • Strong analytical and technical problem-solving ability
• • High standards for data accuracy, reliability, and engineering quality
• • Ability to understand complex data relationships and system dependencies
• • Strong ownership of production pipelines and data products
• • Ability to balance scalability, performance, maintainability, and cost
• • Clear written and verbal communication skills
• • Effective collaboration within distributed technical teams
• • Comfortable independently investigating complex technical problems
• • Curiosity about cloud technologies, AI infrastructure, and evolving data-engineering practices
• • Remote position within the United States
• • Full-time position within a large enterprise technology environment
• • 3+ years of professional data engineering, software engineering, or data-platform experience preferred
• • Familiarity with Git, automated testing, CI/CD, and Infrastructure as Code is advantageous