AWS Data Engineer

• 6–10+ years of experience in Data Engineering / Big Data Engineering.
• Strong hands-on experience with AWS cloud services.
• Strong programming experience in Python.
• Hands-on experience with PySpark / Apache Spark.
• Strong SQL development and database skills.
• Experience developing ETL/ELT data pipelines.
• Experience with AWS Glue, S3, Lambda, EMR, RDS, Redshift, and CloudWatch.
• Experience with Apache Kafka or Confluent Kafka.
• Experience with Apache Airflow or another workflow orchestration platform.
• Strong understanding of data modeling, data warehousing, and distributed data processing.
• Experience working with Parquet, JSON, Avro, and other data formats.
• Experience with Git and CI/CD practices.
• Good understanding of AWS security, IAM, networking, and cloud architecture.

Preferred Skills

• Experience in the financial services / wealth management / banking domain.
• Experience working with Snowflake or Databricks.
• Experience with AWS OpenSearch / Elasticsearch.
• Experience with Terraform or CloudFormation.
• Experience with Docker/Kubernetes.
• Experience with AWS monitoring and observability tools.
• Knowledge of data governance, lineage, metadata management, and data quality frameworks.
• Experience working in Agile/Scrum development environments.

Education

Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field is preferred.

Ideal Candidate

The ideal candidate is a strong AWS Data Engineer with hands-on experience building scalable batch and streaming data pipelines using Python, PySpark, Spark, Kafka, AWS Glue, S3, EMR, Lambda, and SQL. Experience within financial services or wealth management and exposure to modern cloud data platforms will be highly valued.