Neo4j Developer - Graph DBMS (3-8 yrs)

Job Title : NEO 4J Developer.

Location : Gurugram.

Experience Required : 6-8 Years.

Work Type : Contract (6 Months).

Mandatory Skills : NEO 4J.

Job Summary : As a Neo4j Developer, you will be responsible for the design, development, and maintenance of Neo4j graph databases.

You will work closely with cross-functional teams to optimize graph database performance, ensure data integrity, and implement scalable and efficient graph-based solutions to meet business needs.

This role requires strong expertise in Neo4j database management, as well as proficiency in Cypher query language, data modeling, performance tuning, and troubleshooting complex graph database issues.

About Us :

This position is being recruited by Smartwork IT Services, a leading recruitment and product-based company.

In addition to staffing solutions, Smartwork IT Services is involved in developing cutting-edge products like SWITS ATS (Applicant Tracking System) and SWITS HRMS (Human Resource Management Services).

We focus on delivering exceptional value through innovative solutions and top-tier talent acquisition.

Roles & Responsibilities :

- Expected to be an SME.

- Collaborate and manage the team to perform.

- Responsible for team decisions.

- Engage with multiple teams and contribute to key decisions.

- Provide solutions to problems for their immediate team and across multiple teams.

- Lead the effort to design, build, and configure applications.

- Act as the primary point of contact for the project.

- Manage the team and ensure successful project delivery.

- Collaborate with multiple teams to make key decisions.

- Provide solutions to problems for the immediate team and across multiple teams.

Professional & Technical Skills :

Must To Have Skills :

- Proficiency in Neo4j.

- Strong understanding of statistical analysis and machine learning algorithms.

- Experience with data visualization tools such as Tableau or Power BI.

- Hands-on implementing various machine learning algorithms such as linear regression, logistic regression, decision trees, and clustering algorithms.

- Solid grasp of data munging techniques, including data cleaning, transformation, and normalization to ensure data quality and integrity.