Job Title: Data Engineer

Location: New York, NY
Job Type: Long-Term Contract
Work Mode: Hybrid / Onsite
Experience: 7+ Years

Job Description

We are looking for an experienced Data Engineer to design, develop, and maintain scalable data pipelines and modern data platforms. The ideal candidate should have strong hands-on experience with Python, SQL, ETL/ELT, AWS, Databricks, and PySpark.

Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
• Build data ingestion and transformation solutions for structured and unstructured data.
• Develop data processing solutions using Python, PySpark, and SQL.
• Work with AWS data services such as S3, Glue, Redshift, Athena, EMR, and Lambda.
• Develop and optimize Databricks and Apache Spark workloads.
• Build and maintain data lakes, data warehouses, and Lakehouse architectures.
• Perform data modeling and support analytics and reporting requirements.
• Optimize SQL queries and data pipeline performance.
• Implement data quality checks, validation, monitoring, and error handling.
• Work with orchestration tools such as Airflow or Databricks Workflows.
• Collaborate with Data Analysts, Data Scientists, Architects, and business stakeholders.
• Support CI/CD and version control using Git and related tools.

Required Skills

• 7+ years of experience in Data Engineering.
• Strong experience with Python.
• Strong expertise in SQL and query optimization.
• Hands-on experience with ETL/ELT and Data Pipelines.
• Experience with Apache Spark / PySpark.
• Experience with Databricks.
• Strong experience with AWS Cloud.
• Experience with AWS services such as S3, Glue, Redshift, Athena, EMR, and Lambda.
• Experience with Data Lake, Data Warehouse, or Lakehouse architecture.
• Knowledge of data modeling concepts.
• Experience with Git and CI/CD.

Preferred Skills

• Snowflake
• Apache Airflow
• Kafka or Kinesis
• Delta Lake
• dbt
• Terraform
• Docker and Kubernetes
• Financial Services / Banking domain experience

1. Python
2. SQL
3. ETL/ELT & Data Pipelines
4. AWS
5. Databricks + PySpark