Offer summary

Qualifications:

3 to 7 years of experience in data engineering or related fields., Proficiency in at least four GCP services such as Data Flow, BigQuery, and Cloud Functions., Hands-on programming skills in Spark/Scala, Python, or Java., Experience with Ascend.io is non-negotiable..

Key responsabilities:

Build, automate, and optimize data workloads using Ascend.io.

Design and operationalize large-scale data solutions on GCP.

Develop and maintain ETL/ELT data pipelines from ingestion to consumption.

Collaborate with team members and stakeholders to ensure effective communication.

Job description

Job Title: Senior Data Engineer

Job Description:

This role involves building, automating, and optimizing data workloads, and requires a proactive individual with strong problem-solving skills. The position is full-time, requiring 8 hours per day for 4-6 months, with a possible extension.

Key Responsibilities:

Data Workload Management: Use Ascend.io to build, automate, and optimize data workloads.
Enterprise Data Solutions: Design and operationalize large-scale data solutions using GCP services like Data Flow, Data Proc, Pub Sub, BigQuery, Cloud Functions, Composer, and GCS.
ETL/ELT Pipelines: Develop and maintain ETL/ELT data pipelines from ingestion to consumption.
Programming: Apply hands-on programming skills in Spark/Scala (Python/Java).
Data Engineering: Utilize knowledge of Data Lakes, Data Warehouses (Redshift/Hive/Snowflake), integration, and migration.
Communication: Collaborate effectively with team members and stakeholders.
Version Control: Manage code using version control tools (Git/Bitbucket/Code Commit).

Required Skills and Experience:

Ascend.io Expertise: Experience with Ascend.io (Non-negotiable).
Work Experience: 3 to 7 years in data engineering or related fields.
GCP Services: Proficient with at least four GCP services (Data Flow, Data Proc, Pub Sub, BigQuery, Cloud Functions, Composer, GCS).
Programming Skills: Hands-on experience in Spark/Scala (Python/Java).
ETL/ELT Pipelines: Proven experience in building ETL/ELT pipelines.
Data Engineering Knowledge: Understanding of Data Lakes, Data Warehouses, integration, and migration.
Communication: Excellent written and verbal skills.
Version Control: Experience with version control tools (Git/Bitbucket/Code Commit).

Shift Timings: