Snowflake & Python Data Engineer

Requirements

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or related fields.
• 7+ years of hands-on experience in data engineering, with in-depth expertise in Snowflake and Python.
• Proven track record of designing scalable data

Benefits

Additional Information

Job Summary Synechron is seeking a highly experienced Snowflake & Python Data Engineer to design, develop, and support scalable, high-performance data solutions leveraging cloud data platforms. This role involves building robust data pipelines, transforming large datasets, and automating data workflows to enable enterprise analytics and reporting. The ideal candidate will have strong expertise in Snowflake, Python, SQL, and data modeling, collaborating with data engineering, analytics, and business teams to deliver scalable, secure, and efficient data architectures aligned with organizational goals. Software Requirements Required: Extensive hands-on experience with Snowflake for data warehousing, including schemas, views, and performance optimization techniques. Strong proficiency in Python for data processing, automation, and integrations. Advanced skills in SQL / PLSQL for data querying, transformation, and performance tuning. Knowledge of ETL/ELT concepts and data pipeline orchestration tools. Experience with data integration between Snowflake and upstream/downstream systems. Familiarity with cloud platforms (preferably AWS, Azure, or GCP) for deploying and managing data solutions. Experience with version control tools like Git and automation tools in CI/CD pipelines. Preferred: Exposure to Terraform or CloudFormation for infrastructure provisioning. Experience using data orchestration tools such as Apache Airflow or Prefect . Knowledge of data security protocols, role-based access, and compliance standards. Experience with containerization (Docker) and orchestration (Kubernetes) for data workflows. Overall Responsibilities Design, develop, and optimize large-scale data pipelines and transformation workflows on Snowflake and cloud platforms. Build and maintain scalable, efficient, and secure data models and databases supporting analytics and reporting. Develop and fine-tune Python scripts for data automation, validation, and integration tasks. Collaborate with data engineers, analytics teams, and business stakeholders to understand data requirements and deliver insights. Monitor the performance of data pipelines and optimize queries and workloads for efficiency. Implement data quality, governance processes, and security best practices across data platforms. Automate deployment, testing, and infrastructure provisioning using CI/CD and IaC tools. Stay updated on emerging data technologies, tools, and best practices, recommending improvements. Performance Outcomes: Reliable, scalable, and secure data platforms enabling faster insights, better decision-making, and improved operational efficiencies. Technical Skills (By Category) Programming Languages: Essential: Python, SQL, PL/SQL Preferred: Shell scripting, Java, or other languages for automation Data & Database Management: Essential: Snowflake data warehouse, data modeling (star/snowflake schemas) Preferred: NoSQL databases (MongoDB, DynamoDB) Cloud Technologies: Preferred: AWS (S3, Lambda, Glue), Azure, GCP Frameworks & Libraries: Essential: SQLAlchemy, Pandas, NumPy, DataFrames in Python Preferred: Airflow, Apache Spark, PySpark Development Tools & Methodologies: Essential: Git, CI/CD pipelines, Terraform, Docker Preferred: Kubernetes, CloudFormation, DataOps tools Security & Compliance: Strong understanding of data security practices, encryption, role-based access controls, and regulatory standards like GDPR or HIPAA. Experience Requirements Minimum of 7+ years supporting enterprise data systems, with a focus on Snowflake and Python-based data solutions. Proven experience designing, deploying, and managing large-scale data pipelines in cloud environments. Extensive hands-on experience optimizing data queries and models in Snowflake. Demonstrable success building automated data workflows, integrations, and transformations. Experience working in agile, fast-paced enterprise environments, preferably in finance, healthcare, or retail sectors. Day-to-Day Activities Develop, test, and deploy scalable data pipelines on Snowflake integrated with cloud platforms. Write and optimize Python scripts and SQL queries for data ingestion, transformation, and automation. Collaborate with cross-functional teams to understand data needs and deliver reliable solutions. Monitor data pipeline performance and troubleshoot issues in real-time. Perform data quality checks, validation, and security reviews. Automate infrastructure provisioning and deployment processes as part of CI/CD workflows. Document data architecture, schemas, workflows, and best practices. Review and optimize data workflows regularly, incorporating new tools and industry best practices.

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