We are looking for an experienced Data Engineer to build, optimize, and manage scalable data pipelines and architectures. The ideal candidate will have strong expertise in modern data platforms, with hands-on experience in Snowflake and cloud-based data solutions.
- Design, build, and maintain scalable data pipelines and ETL/ELT processes
- Develop and optimize data models and data warehouse solutions
- Work extensively with Snowflake for data storage, transformation, and performance tuning
- Collaborate with BI, analytics, and product teams to deliver clean and reliable datasets
- Ensure data quality, integrity, and governance across systems
- Optimize query performance and cost efficiency in Snowflake
- Integrate data from multiple sources (APIs, databases, third-party systems)
- Implement data security and access controls
RequirementsRequired Skills & Qualifications
- 7+ years of experience in Data Engineering or related roles
- Strong expertise in Snowflake (data modeling, performance tuning, optimization)
- Advanced SQL skills and experience with large-scale data processing
- Hands-on experience with ETL/ELT tools (e.g., Airflow, Informatica, dbt, or similar)
- Experience with cloud platforms such as AWS / Azure / GCP
- Strong understanding of data warehousing concepts (star schema, snowflake schema, etc.)
- Experience with Python or Scala for data processing
- Knowledge of data pipeline orchestration and scheduling
BenefitsPreferred Skills
- Experience with big data technologies (Spark, Hadoop)
- Familiarity with streaming tools (Kafka, Kinesis)
- Experience with CI/CD pipelines and DevOps practices
- Exposure to data governance and data security best practices
- Strong problem-solving and analytical skills
- Ability to work with cross-functional teams
- Good communication and stakeholder management
- High ownership and accountability
Skills Required
- 7+ years of experience in Data Engineering or related roles
- Strong expertise in Snowflake (data modeling, performance tuning, optimization)
- Advanced SQL skills and experience with large-scale data processing
- Hands-on experience with ETL/ELT tools (e.g., Airflow, Informatica, dbt)
- Experience with cloud platforms such as AWS, Azure, or GCP
- Strong understanding of data warehousing concepts (star schema, snowflake schema)
- Experience with Python or Scala for data processing
- Knowledge of data pipeline orchestration and scheduling
- Ensure data quality, integrity, and governance across systems
- Implement data security and access controls
- Experience with big data technologies (Spark, Hadoop)
- Familiarity with streaming tools (Kafka, Kinesis)
- Experience with CI/CD pipelines and DevOps practices
- Exposure to data governance and data security best practices
What We Do
Squareshift is a technology and IT services company that helps organizations with digital transformation, data engineering, cybersecurity, and cloud adoption. It serves clients ranging from VC-backed startups to Fortune 500 companies, operating across the United States, Singapore, and India. Its mission is to act as a trusted partner in building secure, scalable, data-driven, and cloud-enabled business capabilities through integrated technical expertise and global delivery.
