Senior Data Engineer

Client: NBCUniversal

Role: Sr Data Engineer

Location: Englewood Cliffs, NJ onsite 3 days/week

Visa: USC

Contract:W2

Duration: 6-12 month contract to hire

Interview: 2 rounds

• Round 1 Senior Manager/Phone Call
• Round 2 Team/In-Person Interview (Technical). Live coding in Python and PySpark.

Must-haves

• 5-8 years of experience as a Data Engineer
• Python and PySpark experience at the programming (OOP) level
• Experience with Kafka for batch processing and/or streaming pipelines
• Relative experience with Google Cloud Platform Dataproc, Google Cloud Platform Pub/Sub, RabbitMQ, AWS Redis, or Spark Streaming is okay
• Proficiency with AWS utilizing Lambda, S3, SQS, SNS, and Kinesis
• AWS EMR or Databricks experience

Plus

• Airflow and DAG AWS Services
• AWS Certification
• Lead experience and ability to mentor junior developers

Day-to-Day

A Large Media Client is seeking a Data Engineer with strong Python and AWS technical expertise to join their Data Engineering team. The Data Engineer will play a crucial role in designing, implementing, and maintaining scalable data pipelines and solutions on the AWS platform. Your work will involve handling large volumes of diverse data, ensuring its accuracy, and providing real-time streaming pipelines and batch processing. The day-to-day will involve building and optimizing pipelines for processing terabytes of data on a varying increments, including monthly, weekly, daily, hourly. This includes both batch processing (daily schedules, hourly updates) and real-time streaming pipelines. The Data Engineer will work closely with cross-functional teams (Cyber, Cloud Ops, AWS, Databricks, partners, and vendors) to address technical issues and resolutions. The Data Engineer will utilize Terraform to write infrastructure code and AWS services, including but not limited to Lambda, SQS, SNS, S3, and Airflow.

Client: NBCUniversal

Role: Sr Data Engineer

Location: Englewood Cliffs, NJ onsite 3 days/week

Visa: USC

Contract:W2

Duration: 6-12 month contract to hire

Interview: 2 rounds

• Round 1 Senior Manager/Phone Call
• Round 2 Team/In-Person Interview (Technical). Live coding in Python and PySpark.

Must-haves

• 5-8 years of experience as a Data Engineer
• Python and PySpark experience at the programming (OOP) level
• Experience with Kafka for batch processing and/or streaming pipelines
• Relative experience with Google Cloud Platform Dataproc, Google Cloud Platform Pub/Sub, RabbitMQ, AWS Redis, or Spark Streaming is okay
• Proficiency with AWS utilizing Lambda, S3, SQS, SNS, and Kinesis
• AWS EMR or Databricks experience

Plus

• Airflow and DAG AWS Services
• AWS Certification
• Lead experience and ability to mentor junior developers

Day-to-Day

A Large Media Client is seeking a Data Engineer with strong Python and AWS technical expertise to join their Data Engineering team. The Data Engineer will play a crucial role in designing, implementing, and maintaining scalable data pipelines and solutions on the AWS platform. Your work will involve handling large volumes of diverse data, ensuring its accuracy, and providing real-time streaming pipelines and batch processing. The day-to-day will involve building and optimizing pipelines for processing terabytes of data on a varying increments, including monthly, weekly, daily, hourly. This includes both batch processing (daily schedules, hourly updates) and real-time streaming pipelines. The Data Engineer will work closely with cross-functional teams (Cyber, Cloud Ops, AWS, Databricks, partners, and vendors) to address technical issues and resolutions. The Data Engineer will utilize Terraform to write infrastructure code and AWS services, including but not limited to Lambda, SQS, SNS, S3, and Airflow.

Client: NBCUniversal

Role: Sr Data Engineer

Location: Englewood Cliffs, NJ onsite 3 days/week

Visa: USC

Contract:W2

Duration: 6-12 month contract to hire

Interview: 2 rounds

• Round 1 Senior Manager/Phone Call
• Round 2 Team/In-Person Interview (Technical). Live coding in Python and PySpark.

Must-haves

• 5-8 years of experience as a Data Engineer
• Python and PySpark experience at the programming (OOP) level
• Experience with Kafka for batch processing and/or streaming pipelines
• Relative experience with Google Cloud Platform Dataproc, Google Cloud Platform Pub/Sub, RabbitMQ, AWS Redis, or Spark Streaming is okay
• Proficiency with AWS utilizing Lambda, S3, SQS, SNS, and Kinesis
• AWS EMR or Databricks experience

Plus

• Airflow and DAG AWS Services
• AWS Certification
• Lead experience and ability to mentor junior developers

Day-to-Day

A Large Media Client is seeking a Data Engineer with strong Python and AWS technical expertise to join their Data Engineering team. The Data Engineer will play a crucial role in designing, implementing, and maintaining scalable data pipelines and solutions on the AWS platform. Your work will involve handling large volumes of diverse data, ensuring its accuracy, and providing real-time streaming pipelines and batch processing. The day-to-day will involve building and optimizing pipelines for processing terabytes of data on a varying increments, including monthly, weekly, daily, hourly. This includes both batch processing (daily schedules, hourly updates) and real-time streaming pipelines. The Data Engineer will work closely with cross-functional teams (Cyber, Cloud Ops, AWS, Databricks, partners, and vendors) to address technical issues and resolutions. The Data Engineer will utilize Terraform to write infrastructure code and AWS services, including but not limited to Lambda, SQS, SNS, S3, and Airflow.

Client: NBCUniversal

Role: Sr Data Engineer

Location: Englewood Cliffs, NJ onsite 3 days/week

Visa: USC

Contract:W2

Duration: 6-12 month contract to hire

Interview: 2 rounds

• Round 1 Senior Manager/Phone Call
• Round 2 Team/In-Person Interview (Technical). Live coding in Python and PySpark.

Must-haves

• 5-8 years of experience as a Data Engineer
• Python and PySpark experience at the programming (OOP) level
• Experience with Kafka for batch processing and/or streaming pipelines
• Relative experience with Google Cloud Platform Dataproc, Google Cloud Platform Pub/Sub, RabbitMQ, AWS Redis, or Spark Streaming is okay
• Proficiency with AWS utilizing Lambda, S3, SQS, SNS, and Kinesis
• AWS EMR or Databricks experience

Plus

• Airflow and DAG AWS Services
• AWS Certification
• Lead experience and ability to mentor junior developers

Day-to-Day

A Large Media Client is seeking a Data Engineer with strong Python and AWS technical expertise to join their Data Engineering team. The Data Engineer will play a crucial role in designing, implementing, and maintaining scalable data pipelines and solutions on the AWS platform. Your work will involve handling large volumes of diverse data, ensuring its accuracy, and providing real-time streaming pipelines and batch processing. The day-to-day will involve building and optimizing pipelines for processing terabytes of data on a varying increments, including monthly, weekly, daily, hourly. This includes both batch processing (daily schedules, hourly updates) and real-time streaming pipelines. The Data Engineer will work closely with cross-functional teams (Cyber, Cloud Ops, AWS, Databricks, partners, and vendors) to address technical issues and resolutions. The Data Engineer will utilize Terraform to write infrastructure code and AWS services, including but not limited to Lambda, SQS, SNS, S3, and Airflow.