Technical Lead(Job Number: 00070571531)

Earnmodes; India; Hybrid; INR 2,600,000 - 4,000,000; Full time

Job summary

Earnmodes is seeking a Technical Lead to guide data engineering initiatives using Azure Data Factory and Databricks in a hybrid day-shift role in India. The candidate will mentor teams and collaborate with business stakeholders to architect robust data pipelines and analytics solutions.

Prior experience in life and annuities insurance domain is preferred to enhance domain-driven design across enterprise data platforms.

Qualifications

• Extensive hands-on expertise with Azure Data Factory including pipeline development and data flow configurations.
• Experience designing cloud data architectures with storage compute and integration patterns.
• Strong ability to translate analytic requirements into robust Azure-based data solutions.

Responsibilities

• Drive end-to-end design and implementation of scalable data pipelines using Azure Data Factory and Databricks to support enterprise analytics and reporting needs.
• Lead technical solutioning for complex data integration scenarios by defining ingestion transformation and orchestration patterns.
• Coordinate hybrid delivery by planning onsite and remote work to optimize collaboration and milestones.
• Provide technical guidance to data engineers by reviewing code design and deployment approaches to ensure quality security and stability.
• Collaborate with business stakeholders to translate requirements into structured Azure-based data solutions delivering measurable value.

Skills

Data engineering

Mentoring

Stakeholder communication

Tools

Azure Data Factory

Databricks

Job description

Job Description

Job Description – Technical Lead (00070571531)
Job Description
Technical Lead(Job Number:
00070571531)

Description

Job Summary

This hybrid day shift role is for a seasoned technical lead with deep hands on experience in Azure Data Factory and Databricks guiding complex data engineering initiatives for an international organization. The role focuses on architecting robust data pipelines and analytics solutions mentoring technical teams and collaborating with business stakeholders. Experience in life and annuities insurance is preferred to enhance domain driven design and insight generation across enterprise data plat

Responsibilities

Drive end to end design and implementation of scalable data pipelines using Azure Data Factory and Databricks to support enterprise analytics and reporting needs across the organization

Lead technical solutioning for complex data integration scenarios by defining patterns for ingestion transformation and orchestration that ensure reliability performance and maintainability

Coordinate hybrid model delivery activities by planning onsite and remote work schedules that optimize collaboration with cross functional partners and maintain consistent progress on critical milestones

Provide technical guidance to data engineers and developers by reviewing code design artifacts and deployment approaches to uphold high standards of quality security and operational stability

Collaborate with business and product stakeholders by translating analytical and reporting requirements into well structured Azure based data solutions that deliver measurable value to customers and internal teams

Optimize Databricks workloads by tuning clusters jobs and queries to improve cost efficiency execution speed and resource utilization while enforcing best practices for workspace organization and governance

Implement robust monitoring logging and alerting for Azure Data Factory and Databricks jobs by leveraging native tools and dashboards to proactively identify issues and reduce downtime

Ensure data quality and consistency across data pipelines by designing validation rules reconciliation checks and error handling strategies that strengthen trust in curated datasets and downstream analytics

Coordinate secure data access and compliance alignment by working with security and risk partners to apply appropriate controls masking and role based permissions across data platforms

Support project planning and estimation activities by providing realistic effort assessments for data engineering tasks enabling accurate timelines and resource allocation for delivery teams

Partner with architecture and infrastructure groups by aligning solutions with enterprise standards reference architectures and cloud governance guidelines to maintain long term sustainability

Contribute to continuous improvement initiatives by capturing lessons learned researching emerging Azure data services and proposing enhancements that increase productivity and innovation across projects

Engage with domain experts in life and annuities insurance when available by shaping data models metrics and analytics that reflect key business processes and improve decision making for policy and claims outcomes

Qualifications

Demonstrate extensive hands on expertise with Azure Data Factory including pipeline development data flow configurations and integration runtime management for complex enterprise workloads

Apply strong Databricks knowledge by building performant notebooks jobs and workflows that leverage Spark based processing for batch and near real time data transformation scenarios

Bring proven experience in designing cloud data architectures that include storage choices compute strategies and integration patterns aligned with organizational standards and performance expectations

Utilize solid data engineering fundamentals such as modeling ETL design optimization and testing to create resilient data solutions that are easy to maintain and extend over time

Leverage any background in life and annuities insurance to interpret business concepts such as policy lifecycle underwriting claims and actuarial analysis when designing data structures and analytics outputs

Communicate effectively with technical and nontechnical partners by explaining solution approaches dependencies and risks in clear language that supports informed decisions and collaborative planning

Operate comfortably in a hybrid work environment by using collaboration tools disciplined documentation and regular touchpoints to maintain transparency and alignment across onsite and remote participants

Certifications Required

Azure Data Engineer Associate or equivalent cloud data certification preferred

Source: Company Career page