Design, develop, and maintain scalable data pipelines. Transform and analyze data using Python and SQL. Collaborate with analysts, data scientists, and stakeholders to ensure data quality, integrity, and security.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Senior Data Engineer (Remote – US Timings)
Location: Remote (aligned with US time zones)
About Us:
At AirproIT, we deliver high-quality data solutions to clients worldwide. We value innovation, collaboration, and excellence and are looking for talented individuals to join our growing team.
Role Overview:
We are seeking a Senior Data Engineer to design, develop, and maintain scalable data pipelines, manage large datasets, and support data-driven initiatives across our global client base.
Key Responsibilities:
- Design, implement, and maintain ETL/ELT pipelines using Airflow, Azure Data Factory, dbt, or AWS Glue.
- Transform and analyze data using Python and SQL.
- Work with cloud data platforms such as Snowflake, Azure Synapse, or AWS Redshift.
- Build and maintain data lakes/lakehouses using Spark, Flink, or Databricks.
- Design dimensional data models (Star/Snowflake schema), optimize data warehousing solutions, and enhance performance.
- Use Git for version control and CI/CD to automate pipelines.
- Handle real-time data streams via Kafka, Event Hubs, or similar tools.
- Collaborate with analysts, data scientists, and stakeholders to ensure data quality, integrity, and security.
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Qualifications:
- Proven experience as a Data Engineer or similar role.
- Strong experience with ETL/ELT pipeline development and data warehousing.
- Proficiency in SQL and Python for data transformation and analytics.
- Familiarity with cloud ecosystems like Azure, AWS, or GCP.
- Experience with real-time data streaming and data lake/lakehouse architecture is a plus.
- Excellent problem-solving, communication, and collaboration skills.
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What We Offer:
- Fully remote position with flexible hours aligned with US time zones.
- Opportunity to work on challenging projects with global clients.
- Collaborative and innovative work environment.
How to Apply:
If you are passionate about data engineering and want to tackle exciting challenges, apply through LinkedIn or send us a message for more details.
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