Senior Data Engineer- AWS

You should possess a degree in computer science, engineering, or a related field along with 3-4 years of experience in the field. Your primary skillsets should include AWS, Pyspark, SQL, Databricks, and Python. Additionally, you should have experience with data integration and pipeline development, specifically using AWS Cloud services such as Apache Spark, Glue, Kafka, Kinesis, and Lambda in S3 Redshift, RDS, and MongoDB/DynamoDB ecosystems. Experience with Databricks and Redshift is considered a major plus. You must also have proficiency in SQL, especially in the development of data warehouse projects and applications using Oracle and SQL Server. Furthermore, you should have a strong background in Python development, particularly in PySpark within an AWS Cloud environment. Familiarity with SQL and NoSQL databases like MySQL, Postgres, DynamoDB, and Elasticsearch is essential. Experience with workflow management tools such as Airflow and knowledge of AWS cloud services like RDS, AWS Lambda, AWS Glue, AWS Athena, and EMR are also required. Familiarity with equivalent tools in the GCP stack will be considered a plus. Any experience with ETL tools, Github, and DevOps (CI-CD) will be beneficial for this role. Snowflake and Palantir Foundry knowledge is considered a good-to-have skill. Overall, you will be responsible for designing, developing, testing, and supporting data pipelines and applications as an AWS Data Engineer.,