Azure Databricks handson Architect
Indexed description
Role description
Principal Azure Databricks handson Architect
Azure Databricks Data Engineering Lakehouse Architecture
Must Have Skills
Strong experience in designing and developing data pipelines and ETLELT workflows using Azure Databricks
Expertise in Apache Spark PySparkScala and SQL for largescale data processing
Handson experience with Delta Lake and Lakehouse architecture
Experience in building scalable optimized and performant data pipelines
Strong understanding of data modeling data integration and big data processing frameworks
Experience with Azure ecosystem ADLS ADF Synapse
Knowledge of data governance security and data quality frameworks within Databricks
Ability to monitor troubleshoot and optimize Databricks workloads and performance
Experience working with crossfunctional teams for integrating data solutions
Proven experience in architectural design and data engineering strategy planning
Secondary Nice To Have Skills NOT MANDATORY
Experience with machine learning workflows on Databricks MLflow model deployment
Familiarity with Unity Catalog data lineage and governance frameworks
Exposure to CICD DevOps and orchestration tools Airflow Azure DevOps
Experience with streaming frameworks Kafka Structured Streaming
Knowledge of BI tools such as Power BI
Domain exposure in Insurance Financial Services
Experience in evaluating and adopting emerging data engineering tools and technologies
Soft Skills
Strong technical leadership and mentoring abilities
Excellent stakeholder management and requirement translation skills
Effective communication and collaboration across business and technical teams
Problemsolving mindset with focus on performance optimization and innovation
Ability to drive best practices code quality and continuous improvement initiatives
Strategic thinking with ability to contribute to enterprise data architecture decisions
Qualifying Questions
1Can you describe your experience in designing endtoend data pipelines using Azure Databricks BronzeSilverGold architecture What scale and complexity did you handle
2How have you optimized performance cost compute query efficiency in Databricks workloads Please share a specific example
3Have you led architecture decisions or mentored teams on Databricks best practices Can you elaborate on your role and impact
Variable Compensation: This position includes a bonus or variable payout component based on individual and organizational performance.
Actual compensation within the range will be dependent upon the individual's skills, experience, performance and internal equity.
Benefits/perks listed below may vary depending on the nature of your employment with LTIMindtree (“LTIM”):
Benefits and Perks:
- Comprehensive Medical Plan Covering Medical, Dental, Vision
- Short Term and Long-Term Disability Coverage
- 401(k) Plan with Company match
- Life Insurance
- Vacation Time, Sick Leave, Paid Holidays
- Paid Paternity and Maternity Leave
The range displayed on each job posting reflects the minimum and maximum salary target for the position across all US locations. Within the range, individual pay is determined by work location and job level and additional factors including job-related skills, experience, and relevant education or training. Depending on the position offered, other forms of compensation may be provided as part of overall compensation like an annual performance-based bonus, sales incentive pay and other forms of bonus or variable compensation.
Disclaimer: The compensation and benefits information provided herein is accurate as of the date of
this posting.
LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our
employment decisions are made without regard to race, color, creed, religion, sex (including
pregnancy, childbirth or related medical conditions), gender identity or expression, national origin,
ancestry, age, family-care status, veteran status, marital status, civil union status, domestic
partnership status, military service, handicap or disability or history of handicap or disability, genetic
information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation
or preference, or any other characteristic protected by applicable federal, state, or local law, except
where such considerations are bona fide occupational qualifications permitted by law.
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