Data Engineer

Shashwath Solution; Pune District; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Shashwath Solution in Pune, Maharashtra, is seeking a Data Engineer to design, develop, and maintain scalable data pipelines, ensuring data quality and integrity across systems. The role involves collaborating with data analysts and scientists to meet diverse data requirements.

Introducing dashboards and reports, optimizing ETL processes for performance and reliability, and maintaining database health with strong security. A proactive learner will thrive in this environment.

Qualifications

• Experience with ETL processes and data pipelines.
• Strong SQL skills for large datasets and query optimization.
• Ability to design and maintain dashboards or reports.
• Documentation of data workflows and technical specs.

Responsibilities

• Design, develop, and implement scalable data pipelines.
• Ensure data quality and integrity through testing and monitoring.
• Optimize ETL processes for performance and reliability.
• Manage and maintain databases with high availability and security.
• Troubleshoot database issues and improve performance.
• Collaborate with data analysts, scientists, and stakeholders.
• Provide support for data-related technical issues and solutions.
• Document data workflows and technical processes.
• Develop simple reports or dashboards to visualize key metrics.

Skills

ETL Concepts

Pipeline Design

Relational DBs

Data Visualization

Query Optimization

Testing & Documentation

Tools

MySQL

PostgreSQL

Oracle

MS SQL Server

Tableau

Power BI

Hadoop

Spark

Job description

Technical Skills Required

• ETL Concepts: Strong understanding of Extract, Transform, Load (ETL) processes.
• ETL Concepts: Ability to design, develop, and maintain robust ETL pipelines.
• Database Fundamentals: Proficiency in working with relational databases (e.g., MySQL, PostgreSQL, Oracle, or MS SQL Server).
• Database Fundamentals: Knowledge of database design and optimization techniques.
• Basic Data Visualization: Ability to create simple dashboards or reports using visualization tools (e.g., Tableau, Power BI, or similar).
• Query Optimization: Expertise in writing efficient, optimized queries to handle large datasets.
• Testing and Documentation: Experience in validating data accuracy and integrity through rigorous testing.
• Testing and Documentation: Ability to document data workflows, processes, and technical specifications clearly.

Key Responsibilities

• Data Engineering Tasks: Design, develop, and implement scalable data pipelines to support business needs.
• Data Engineering Tasks: Ensure data quality and integrity through testing and monitoring.
• Data Engineering Tasks: Optimize ETL processes for performance and reliability.
• Database Management: Manage and maintain databases, ensuring high availability and security.
• Database Management: Troubleshoot database-related issues and optimize performance.
• Collaboration: Work closely with data analysts, data scientists, and other stakeholders to understand and deliver on data requirements.
• Collaboration: Provide support for data-related technical issues and propose solutions.
• Documentation and Reporting: Create and maintain comprehensive documentation for data workflows and technical processes.
• Documentation and Reporting: Develop simple reports or dashboards to visualize key metrics and trends.
• Learning and Adapting: Stay updated with new tools, technologies, and methodologies in data engineering.
• Learning and Adapting: Adapt quickly to new challenges and project requirements.

Additional Requirements

• Strong communication skills, both written and verbal.
• Analytical mindset with the ability to solve complex data problems.
• Quick learner and willingness to adopt new tools and technologies as needed.
• Flexibility to work in shifts, if required.

Preferred Skills (Not Mandatory)

• Experience with cloud platforms (e.g., AWS, Azure, or GCP).
• Familiarity with big data technologies such as Hadoop or Spark.
• Basic understanding of machine learning concepts and data science workflows.