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Premium Employer

Infinite Computer Solutions

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3.3

based on 1.3k Reviews

241 Infinite Computer Solutions Jobs

Specialist

Infinite Computer Solutions India Pvt. Ltd.

3.3

based on 1.3k Reviews

8-13 years

Bangalore / Bengaluru

1 vacancy

Specialist

Infinite Computer Solutions

posted 4d ago

Job Role Insights

Flexible timing

Key skills for the job

SQL Automation Testing Machine Learning Front End Javascript Scheduling

+ 4 more

Job Description

This requirement is for Raju L-SOW22-CR02

An ETL (Extract, Transform, Load) Developer with expertise in BigQuery , JavaScript , and GitHub typically focuses on designing and implementing data workflows, particularly those that involve large-scale data processing and storage in Google BigQuery . They integrate various data sources, transform data according to business requirements, and load it into databases or other destinations. Below is a breakdown of how these skills are used:
1. BigQuery Expertise

Data Extraction and Loading : BigQuery is a serverless, highly scalable data warehouse solution. As an ETL developer, you'll use BigQuery's SQL-like syntax to interact with large datasets, extracting data from various sources such as CSV, JSON, or databases, and loading it into BigQuery tables.
Transformations : Use SQL and BigQuery s built-in functions to perform data transformations, like aggregations, data cleaning, and enriching datasets before they are loaded into final destinations or further processing.
Optimizing Performance : As BigQuery is designed for large-scale data analytics, you ll need to optimize queries for cost and performance. Techniques include partitioning and clustering tables, writing efficient SQL, and understanding BigQuery s pricing model to avoid unnecessary costs.
Automation : Automate ETL workflows using tools like Cloud Composer (Apache Airflow), Cloud Functions , or Dataflow .

2. JavaScript Skills

Custom Transformations : JavaScript can be used for custom transformations or preprocessing steps within the ETL pipeline. For example, you might write JavaScript code for data validation, complex transformations, or data enrichment before loading it into BigQuery.
Scripting and Automation : JavaScript can be used for automating parts of the ETL process, including data extraction or loading. Tools like Google Cloud Functions allow you to write JavaScript to automate workflows in the cloud.
Client-Side Interactions : JavaScript might be used in building front-end applications or dashboard tools that interact with the BigQuery data and provide real-time insights or visualizations.

3. GitHub for Version Control

Source Code Management : Use GitHub for version control, managing the ETL scripts, JavaScript code, and BigQuery SQL queries. It's important to maintain code quality, handle collaboration with team members, and ensure code is deployed smoothly.
CI/CD Pipelines : Integrate GitHub with CI/CD tools (like Jenkins, GitHub Actions, or Google Cloud Build) to automate the deployment of ETL processes, ensuring that code changes are tested and deployed automatically into production environments.
Collaboration and Documentation : Collaborate with other team members using GitHub issues and pull requests. Document your ETL workflows, code changes, and best practices for maintaining and optimizing data pipelines.

4. Additional Skills/Tools

Data Pipeline Frameworks : Knowledge of frameworks like Apache Airflow , Cloud Composer , or Google Cloud Dataflow for orchestrating and scheduling ETL workflows.
Data Integration Tools : Familiarity with integration tools such as Fivetran , Talend , or Apache NiFi for extracting and loading data into BigQuery.
Cloud Services : Understanding of other Google Cloud Platform (GCP) services like Cloud Storage , Cloud Functions , Cloud Pub/Sub , and BigQuery ML for machine learning integration into data workflows.

Skills Summary:

BigQuery : SQL-based data manipulation, performance tuning, automation, cost optimization.
JavaScript : Custom transformations, scripting, cloud function integration.
GitHub : Version control, CI/CD pipelines, collaboration, and code deployment.