Sr. Data Engineer - NYC, NY ONSITE
Role: Sr. Data Engineer
Location: NYC, NY ONSITE
Duration: 12 Months Contract
Interview Process: Face 2 Face
Experience: 10+ Years
Job Description :-
Required Skills:
1.Proficiency in data engineering programming languages (preferably Python, alternatively Scala or Java)
- Proficiency in atleast one cluster computing frameworks (preferably Spark, alternatively Flink or Storm)
- Proficiency in atleast one cloud data lakehouse platforms (preferably AWS data lake services or Databricks, alternatively Hadoop), atleast one relational data stores (Postgres, Oracle or similar) and atleast one NOSQL data stores (Cassandra, Dynamo, MongoDB or similar)
Proficiency in atleast one scheduling/orchestration tools (preferably Airflow, alternatively AWS Step Functions or similar)
- Proficiency with data structures, data serialization formats (JSON, AVRO, Protobuf, or similar), big-data storage formats (Parquet, Iceberg, or similar), data processing methodologies (batch, micro-batching, and stream), one or more data modelling techniques (Dimensional, Data Vault, Kimball, Inmon, etc.), Agile methodology (develop PI plans and roadmaps), TDD (or BDD) and CI/CD tools (Jenkins, Git,)
Strong organizational, problem-solving and critical thinking skills; Strong documentation skills
Preferred skills:
Experience using AWS Bedrock APIs
Knowledge of Generative AI concepts (such as RAG, Vector embeddings, Model fine tuning, Agentic AI)
Experience in IaC (preferably Terraform, alternatively AWS cloud formation)
Role: Sr. Data Engineer
Location: NYC, NY ONSITE
Duration: 12 Months Contract
Interview Process: Face 2 Face
Experience: 10+ Years
Job Description :-
Required Skills:
1.Proficiency in data engineering programming languages (preferably Python, alternatively Scala or Java)
- Proficiency in atleast one cluster computing frameworks (preferably Spark, alternatively Flink or Storm)
- Proficiency in atleast one cloud data lakehouse platforms (preferably AWS data lake services or Databricks, alternatively Hadoop), atleast one relational data stores (Postgres, Oracle or similar) and atleast one NOSQL data stores (Cassandra, Dynamo, MongoDB or similar)
Proficiency in atleast one scheduling/orchestration tools (preferably Airflow, alternatively AWS Step Functions or similar)
- Proficiency with data structures, data serialization formats (JSON, AVRO, Protobuf, or similar), big-data storage formats (Parquet, Iceberg, or similar), data processing methodologies (batch, micro-batching, and stream), one or more data modelling techniques (Dimensional, Data Vault, Kimball, Inmon, etc.), Agile methodology (develop PI plans and roadmaps), TDD (or BDD) and CI/CD tools (Jenkins, Git,)
Strong organizational, problem-solving and critical thinking skills; Strong documentation skills
Preferred skills:
Experience using AWS Bedrock APIs
Knowledge of Generative AI concepts (such as RAG, Vector embeddings, Model fine tuning, Agentic AI)
Experience in IaC (preferably Terraform, alternatively AWS cloud formation)
