Inshorts - Data Engineer
1 week ago
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
We're seeking a skilled Data Engineer to join our team and build robust data infrastructure. You'll design, develop,
and maintain data pipelines to support our data-driven initiatives.
Responsibilities
● 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).
● Data Warehouse Management: Manage and optimize data warehouses for performance and scalability,
ensuring data integrity and quality.
● Data Modeling: Create and maintain data models that align with business requirements and support analytical
needs.
● SQL Optimization: Write optimized SQL queries to extract data efficiently and support complex analytical
tasks.
● Data Quality Assurance: Implement data quality checks and validation processes to ensure data accuracy
and consistency.
● Report Generation: Develop and maintain reports and dashboards to provide actionable insights to
stakeholders.
● Collaboration: Work closely with data analysts, data scientists, and business teams to understand
requirements and deliver data-driven solutions.
Requirements
● 4+ years of 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., Tableau, Power BI, Looker Pro).
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