Note: The job is a remote job and is open to candidates in USA. Aptonet is seeking an experienced Data Engineer with strong expertise in cloud migration and modern data platform architecture. The role involves designing, implementing, and optimizing robust data pipelines to support enterprise analytics and data-driven decision-making.
Responsibilities
- Lead and support migration of on-premise data platforms to cloud environments, with preference for Teradata to AWS migrations
- Design scalable cloud-native data architectures ensuring security, performance, and cost efficiency
- Design, build, and maintain production-grade data pipelines across the full data lifecycle
- Implement ingestion frameworks to collect data from databases, APIs, logs, and other internal/external sources
- Develop transformation and enrichment processes to convert raw data into analytics-ready datasets
- Build optimized loading processes for data warehouses and data lakes
- Implement data validation, reconciliation, and quality control mechanisms
- Leverage Databricks and Apache Spark to develop scalable batch and streaming data workflows
- Optimize Spark workloads for performance and cost efficiency
- Utilize modern lakehouse principles for structured and semi-structured data processing
- Implement monitoring, alerting, and performance tuning for production pipelines
- Establish data governance best practices, including access control, lineage, and compliance
- Ensure data security standards are maintained across environments
- Design and implement ETL/ELT frameworks for large-scale enterprise data warehouses
- Optimize data ingestion and transformation processes for high-volume environments
Skills
- Bachelor's or Master's degree in Computer Science, Information Systems, or related field
- Proven experience as a Data Engineer with hands-on pipeline development
- Strong experience in cloud environments (AWS preferred; Azure or GCP acceptable)
- Experience with Teradata and/or large-scale data warehouse migrations
- Advanced knowledge of Databricks and Apache Spark
- Strong understanding of ETL/ELT methodologies in enterprise data environments
- Experience with big data technologies such as Hadoop, Spark, HBase, or Teradata
- Proficiency in SQL and programming languages such as Python or Java
- Experience with distributed storage systems, data lakes, and modern warehouse architectures
- Strong analytical, troubleshooting, and problem-solving skills
- Excellent communication and collaboration abilities
Company Overview
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