Back to search
Listing unavailableData & AnalyticsHybrid

Data Engineer

ShyftLabs · Hybrid

This listing is no longer verified as available.

MeritLog keeps this source-backed description for reference. Availability is not verified, and there is no application link here.

Last checked by MeritLog September 12, 2026Source: LeverSource version: lever-postings-v1

Source: the employer's Lever job board. Open the original listing for current details. Availability is not verified for this retained page.

Job details

Work model
Hybrid
Salary
Not listed by source
Location
Coimbatore
Occupation
Database Architects(O*NET 15-1243.00)

What the role asks for

What they're asking for

  • 2–4 years of experience in a Data Engineering roleExperience
  • Strong proficiency in Python and SQLSkill
  • Hands-on experience with Apache SparkSkill
  • Prior experience working on client-based projects (mandatory)Skill
  • Ability to work across both support and development responsibilitiesSkill
  • Strong problem-solving and communication skills for client-facing situationsSkill
  • Experience working with DatabricksSkillPreferred
  • Familiarity with AWS Cloud services (e.g., S3, Glue, EMR, Lambda, Redshift)SkillPreferred
  • Exposure to CI/CD pipelines for data engineering workflowsSkillPreferred
  • Experience with workflow orchestration tools (e.g., Airflow)SkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

Position Overview:   We are seeking a Data Engineer to join a client-focused engagement, with responsibilities split evenly between production support and technical/development work. This role requires 2–4 years of hands-on experience in data engineering, strong proficiency in Python, SQL, and Spark, and prior exposure to client-based project environments. The ideal candidate will be comfortable balancing operational support duties with building and optimizing data pipelines. Job Responsibilities: • Provide day-to-day support (50%) for existing data pipelines, jobs, and platforms -monitoring, troubleshooting, and resolving issues to ensure smooth operations • Design, build, and maintain (50%) scalable data pipelines and ETL/ELT workflows using Python, SQL, and Spark • Collaborate with cross-functional and client teams to understand data requirements and translate them into technical solutions • Perform root-cause analysis on data/pipeline issues and implement fixes with minimal downtime • Optimize existing data workflows for performance, reliability, and cost-efficiency • Document processes, pipeline architecture, and support runbooks for knowledge continuity • Participate in on-call/support rotations as needed for the client engagement • Work with Databricks and/or AWS cloud environments where applicable to build or support data solutions Basic Qualifications: • 2–4 years of experience in a Data Engineering role • Strong proficiency in Python and SQL • Hands-on experience with Apache Spark • Prior experience working on client-based projects (mandatory) • Ability to work across both support and development responsibilities • Strong problem-solving and communication skills for client-facing situations Preferred Skills: • Experience working with Databricks • Familiarity with AWS Cloud services (e.g., S3, Glue, EMR, Lambda, Redshift) • Exposure to CI/CD pipelines for data engineering workflows • Experience with workflow orchestration tools (e.g., Airflow) We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

Keep exploring

Available Data & Analytics roles

These current listings are available to explore now.

Search all jobs

Privacy choices

Analytics and advertising stay off unless you allow them. Private data stays out.

Read the privacy notice