Account Manager - Data Management

Job Description:

Key Responsibilities:

Data Pipeline Development:

• Design build and maintain scalable data pipelines to efficiently process and transform large volumes of structured and unstructured data.
• Work with Python to develop ETL scripts and integrate data from various sources into cloudbased storage solutions (such as Google Cloud Storage or BigQuery.
• Ensure data quality integrity and consistency by implementing automated data validation and testing processes.

SQL & Database Management:

• Develop complex SQL queries for data extraction transformation and loading (ETL) to support business intelligence and analytics efforts.
• Optimize and manage cloudbased relational databases and data warehouses such as BigQuery ensuring performance scalability and cost efficiency.

Cloud Infrastructure (GCP):

• Design and manage data storage solutions using Google Cloud Platform tools including BigQuery Google Cloud Storage and Dataflow.
• Implement cloudbased solutions for data ingestion transformation and storage ensuring that data processing workflows are highly available and faulttolerant.
• Work with GCP services like Dataflow Cloud Pub/Sub and Cloud Functions to build and manage realtime and batch data pipelines.

Collaboration with Data Scientists and Analysts:

• Work closely with data scientists and business intelligence teams to ensure the availability and accessibility of the data needed for advanced analytics reporting and machine learning.
• Provide clean transformed datasets for use in predictive modeling data analytics and reporting.

Performance Optimization:

• Monitor and optimize the performance of data pipelines and cloud storage solutions.
• Implement best practices for managing data in the cloud including performance tuning cost optimization and data governance.

Required Skills and Qualifications:

• Experience: 3 years of experience in data engineering with a focus on Python SQL and cloudbased platforms.
• Python: Strong experience with Python for building ETL processes automation scripts and data transformations.
• SQL: Advanced knowledge of SQL for querying and managing large datasets working with relational databases and optimizing queries.
• GCP: Proficiency with Google Cloud Platform (GCP) particularly BigQuery Google Cloud Storage Dataflow Cloud Pub/Sub and other GCP data services.
• Data Pipeline Development: Experience in designing and implementing endtoend data pipelines that process and transform data for analytics and reporting.
• Data Warehousing: Experience working with cloudbased data warehousing solutions like BigQuery and integrating them with various data sources.
• Version Control: Familiarity with version control systems such as Git for code management and collaboration.

Preferred Qualifications:

• ETL Tools: Experience with ETL tools (e.g. Apache Airflow Talend or similar) for managing data workflows.
• Machine Learning: Knowledge of machine learning frameworks such as TensorFlow or PyTorch especially for data preprocessing tasks.
• Data Governance: Understanding of data governance and best practices for data security privacy and compliance.
• Other Cloud Platforms: Familiarity with other cloud platforms (e.g. AWS Azure) for crossplatform compatibility.

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