Python Developer/ Data Analyst/ Data Engineer

Role & Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using Python, PySpark, SQL, AWS Glue, Airflow, and related technologies.
• Extract, transform, and load data from multiple sources into data lakes and data warehouses such as Amazon Redshift, Snowflake, and Azure Synapse.
• Develop and optimize complex SQL queries, data models, and data integration processes to support business reporting and analytics.
• Build and maintain cloud-based data solutions on AWS and Azure platforms using services such as AWS Glue, Lambda, EMR, Athena, Azure Databricks, and Azure Data Factory.
• Collaborate with business stakeholders, analysts, and development teams to gather requirements and deliver data-driven solutions.
• Perform data validation, data quality checks, and troubleshooting to ensure data accuracy and reliability.
• Develop Python-based applications, automation scripts, APIs, and data processing frameworks.
• Monitor and optimize performance of ETL jobs, Spark workloads, and cloud resources.
• Support data analytics, dashboarding, and reporting initiatives by providing clean and reliable datasets.
• Follow best practices in coding, testing, version control, documentation, and Agile development methodologies. Preferred Candidate Profile
• Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Engineering, or a related field.
• 3-8 years of experience in Data Engineering, Data Analytics, Python Development, or related domains.
• Strong proficiency in Python, SQL, and PySpark.
• Hands-on experience with AWS services including AWS Glue, Athena, Redshift, Lambda, and EMR.
• Experience with workflow orchestration tools such as Apache Airflow.
• Knowledge of cloud data warehouses such as Snowflake and Amazon Redshift.
• Experience with Azure technologies including Azure Databricks, Azure Data Factory, and Azure Synapse Analytics is preferred.
• Strong understanding of ETL/ELT concepts, data modeling, data warehousing, and big data processing.
• Familiarity with Agile methodologies, Git, CI/CD processes, and cloud-native architectures.
• Good analytical, problem-solving, and communication skills.
• Ability to work independently as well as collaboratively in a fast-paced environment. Perks and Benefits
• Competitive salary and performance-based incentives.
• Hybrid/Remote work opportunities.
• Health insurance and wellness benefits.
• Learning and certification support for AWS, Azure, Snowflake, Databricks, and other technologies.
• Career growth opportunities with exposure to enterprise-scale data platforms.
• Flexible work environment and employee-friendly policies.
• Access to the latest cloud, analytics, and big data technologies.
• Employee recognition and rewards programs.
• Paid leaves, holidays, and work-life balance initiatives.
• Opportunity to work on cutting-edge Data Engineering, Analytics, and Python development projects.