Note: The job is a remote job and is open to candidates in USA. Success Recruitments is recruiting for an employer not identified in the posting. The Data Engineer will build and maintain cloud-based data pipelines and platforms supporting analytics, enterprise applications, machine learning, and AI, while improving data quality, reliability, security, and governance.
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
Skills
- 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
- 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
Benefits
- Annual performance incentives
- Equity or long-term incentives where applicable
- Medical, dental, and vision coverage
- Retirement savings with employer contributions
- Paid time off and company holidays
- Paid parental and family leave
- Life and disability coverage
- Remote-work support
- Professional certifications and technical-development resources
- Wellness and employee-assistance programs
- Remote position within the United States
Company Overview