Data Engineer

Company Profile:

Inshorts is a leading tech company specializing in short-format informational content. Our platform delivers concise and engaging news stories and hyperlocal updates to users in a variety of formats.

Role : Data Engineer & Analyst

We're seeking a skilled Data Engineer & Analyst to join our team and build robust data infrastructure. You'll design, develop, and maintain data pipelines to support our data-driven initiatives.

Responsibilities

1. ETL Pipeline Development: Design, develop, and maintain efficient ETL pipelines to extract, transform, and load data from various sources into data warehouses (e.g., BigQuery, Redshift).
2. Data Warehouse Management: Manage and optimize data warehouses for performance and scalability, ensuring data integrity and quality.
3. Data Modeling: Create and maintain data models that align with business requirements and support analytical needs.
4. SQL Optimization: Write optimized SQL queries to extract data efficiently and support complex analytical tasks.
5. Data Quality Assurance: Implement data quality checks and validation processes to ensure data accuracy and consistency.
6. Report Generation: Develop and maintain reports and dashboards to provide actionable insights to stakeholders.
7. Collaboration: Work closely with data analysts, data scientists, and business teams to understand requirements and deliver data-driven solutions.

Requirements

• Experience in data engineering or a related field.
• Bachelor's degree in mathematics, computer science, or statistics.
• Strong proficiency in SQL and Python, with a focus on ETL tools and libraries (e.g., Airflow, Spark, Pandas).
• Experience with cloud-based data platforms (e.g., AWS, GCP , Azure) and data warehousing solutions (e.g.,
• BigQuery, Redshift).
• Familiarity with data modeling concepts, including dimensional and normalized modeling.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.

Preferred Qualifications

• Experience with cloud-based data platforms (e.g., GCP , AWS, Azure).
• Experience with data warehousing solutions (e.g., BigQuery , Redshift , Snowflake).
• Knowledge of machine learning and artificial intelligence.
• Experience with data visualization tools (e.g., T ableau, Power BI, Looker Pro).