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Tier-1 brand, mid-level generalist data role in metro with broad cloud and SQL requirements.
Core data engineering skills (SQL, Python, Spark, cloud) are transferable across industries.
Explicit 5–7 years plus mandatory Snowflake/Databricks, cloud, SQL and CI/CD requirements.
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Design, develop, and manage scalable data pipelines and advanced data structures for analytics, reporting, and downstream applications.
Ensure data quality, governance, and lineage across cloud environments using platforms like Snowflake, Databricks, and distributed processing frameworks such as Apache Spark.
Collaborate with cross-functional teams, support junior engineers, and enhance internal data engineering tools and automation frameworks.
4-7 years of experience in Data Engineering.
Strong proficiency in advanced SQL query writing and optimization.
Experience with Python or similar programming languages and cloud platforms like AWS, GCP, or Azure.
Familiarity with Snowflake/Databricks, distributed computing frameworks, workflow orchestration tools (e.g., dbt, Airflow), and CI/CD processes.
Experienced in building and optimizing data pipelines in cloud-based environments with strong programming and SQL skills.
Capable of independently handling complex data engineering tasks while guiding juniors and contributing to team best practices.
Comfortable working with modern data warehousing technologies and enhancing data processing efficiency, quality, and governance.