Data Engineer

Hackajob; Bhubaneshwar, Bhopal, Delhi; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Hackajob seeks a Data Engineer to design, develop and maintain data solutions for generation, collection and processing. You will build efficient data pipelines and ensure data quality across systems to enable smooth migration and deployment.

Responsibilities include optimizing workflows, collaborating with cross-functional teams, and documenting data processes for stakeholders. Strong PySpark skills and a focus on scalability are essential.

Qualifications

• Minimum 3 years of PySpark experience.
• Experience building data pipelines and ETL workflows.
• Strong understanding of distributed computing and big data frameworks.
• Ability to troubleshoot and optimize data processing jobs.
• Familiarity with data storage solutions and data modeling concepts.
• Knowledge of data quality assurance and validation techniques.

Responsibilities

• Serve as SME and work independently.
• Actively participate in team discussions.
• Propose solutions to work-related problems.
• Collaborate with cross-functional teams to design scalable data solutions.
• Monitor and optimize data workflows for performance and reliability.
• Document data processes and communicate with stakeholders.
• Mentor junior team members by sharing knowledge.

Skills

PySpark

Data pipelines

ETL workflows

Distributed computing

Data quality

Job description

Project Role Description :

Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.

Must have skills :

PySpark

Summary:

As a Data Engineer, your typical day involves designing, developing, and maintaining comprehensive data solutions that support the generation, collection, and processing of data. You will be responsible for creating efficient data pipelines that facilitate smooth data flow across various systems. Ensuring the accuracy and quality of data is a key part of your role, along with implementing processes to extract, transform, and load data effectively. Your work enables seamless data migration and deployment, supporting the broader data infrastructure and analytics needs of the organization.

Roles & Responsibilities:

• Expected to perform independently and become an SME.
• Required active participation/contribution in team discussions.
• Contribute in providing solutions to work related problems.
• Collaborate with cross-functional teams to understand data requirements and deliver scalable solutions.
• Monitor and optimize data workflows to improve performance and reliability.
• Document data processes and maintain clear communication with stakeholders.
• Assist junior team members by sharing knowledge and providing guidance.

Professional & Technical Skills:

• Must To Have Skills: Proficiency in PySpark.
• Experience in building and managing data pipelines and ETL workflows.
• Strong understanding of distributed computing and big data frameworks.
• Ability to troubleshoot and optimize data processing jobs for efficiency.
• Familiarity with data storage solutions and data modeling concepts.
• Knowledge of data quality assurance and validation techniques.

Additional Information:

• The candidate should have minimum 3 years of experience in PySpark.