Vice President - Senior Data Analyst
Evalueserve · Raleigh, NC · 4 wk ago
OTHRFull-time
We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title. Must not include Job ID etc. Must preserve all substantive info, remove boilerplate like EEO, navigation, cookie, application instructions, etc. Must not create sections with filler like "commensurate with experience". So we need to parse the posting.
Let's extract content:
- About the role: The job summary paragraph: "We are seeking a senior Data Architect with 15-20 years of experience and strong expertise in Databricks, GCP, cloud data platforms, the Hadoop ecosystem, and modern ETL/ELT architecture. The role will define enterprise data strategy, design scalable Lakehouse solutions, lead data modernization initiatives, and enable analytics, AI/ML, and business intelligence use cases. In addition, the role will architect and guide enterprise data, analytics, and AI solutions on Google Cloud Platform (GCP)." That's substantive.
- Responsibilities: The list under "Key Responsibilities". It's a series of sentences, each starting with a verb. We can format as
- each bullet.
List items:
1. Design and drive enterprise-scale data architecture using Databricks Lakehouse, Apache Spark, Delta Lake, and cloud-native data platforms.
2. Lead data platform modernization from legacy Hadoop/data warehouse environments to modern Lakehouse and cloud architecture.
3. Defining architecture standards for data ingestion, ETL/ELT, data modeling, data warehousing, governance, security, and performance optimization.
4. Build architecture for batch, near real-time, and streaming data pipelines using Spark, Kafka/Event Hubs/Kinesis, Auto Loader, and workflow orchestration tools.
5. Work with business leaders, product teams, data engineers, platform teams, and analytics teams to translate business needs into scalable technical solutions.
6. Guide teams on data quality, metadata management, data lineage, cost optimization, observability, CI/CD, and production support best practices.
7. Provide technical leadership, review solution designs, mentor engineering teams, and support pre-sales or stakeholder discussions where required.
8. Serve as a trusted technical advisor to clients on data strategy, architecture, engineering, analytics, and AI solutions on Google Cloud.
9. Design scalable, secure, resilient, and cost-optimized GCP architectures using BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Composer, Dataplex, Vertex AI, and Gemini.
10. Lead GCP migration and modernization initiatives, including data warehouses, data lakes, batch and streaming pipelines, governance, security, and performance optimization.
11. Support client discovery, solutioning, RFP responses, proposals, presentations, proof-of-concepts, and smooth handover from pre-sales to delivery for GCP engagements.
Also there is a line: "Enterprise data architecture, Databricks Lakehouse, cloud data platforms, modernization, governance, and analytics enablement, plus GCP data strategy, cloud modernization, and client solutioning." Might be a summary but could be considered part of responsibilities? It's a phrase; maybe treat as bullet? But it's not a full sentence; might be considered filler? It's still substantive but could be part of responsibilities. We'll include as bullet.
Then: "Databricks, Apache Spark, Delta Lake, Hadoop ecosystem, ETL/ELT, cloud data platforms, streaming, data governance, and DevOps, Google Cloud, BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Composer, Dataplex, Vertex AI, and Gemini" This looks like a list of technologies; maybe part of skills? We'll treat as Skills section.
Now Requirements: The posting has "Required Qualifications" list. That's likely Requirements. Also "Preferred Qualifications". Could be separate sections: Requirements (mandatory) and Preferred Qualifications (optional). The instruction says use headings like Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We have both Required and Preferred; we could combine into Requirements (maybe include both required and preferred). But better to have Requirements for required, and Qualifications for preferred? However they said "Qualifications" as a heading. Could treat Required Qualifications as Requirements, and Preferred Qualifications as Qualifications (or maybe Skills). But we also have Skills section for technologies.
Let's decide:
- About the role: job summary.
- Responsibilities: key responsibilities list.
- Requirements: Required Qualifications list.
- Qualifications: Preferred Qualifications list.
- Skills: list of technologies (maybe combine Databricks etc). Could also include "Strong hands-on experience with Databricks, Apache Spark, PySpark or Scala, Spark SQL, Delta Lake, Databricks Workflows, and Databricks SQL." etc. But those are already in Required Qualifications. To avoid duplication, we should not repeat same content. The instruction: Preserve ALL substantive information; do NOT invent or summarize away detail. So we need to include all info, but we can organize into sections without duplication? If we split, we might duplicate content across sections, which would be repeating info. That's allowed? It says preserve all substantive information; not explicitly forbid duplication, but better to avoid redundancy. However we need to fit into headings; we could put all required qualifications under Requirements, and preferred under Qualifications, and skills maybe not needed separately if already covered. But the instruction says "Prefer a few substantive sections over many thin ones." So maybe we combine Required and Preferred into Requirements (or Qualifications) and skip Skills. But we have a distinct list of technologies that appears after responsibilities: "Enterprise data architecture, Databricks Lakehouse, cloud data platforms, modernization, governance, and analytics enablement, plus GCP data strategy, cloud modernization, and client solutioning.Databricks, Apache Spark, Delta Lake, Hadoop ecosystem, ETL/ELT, cloud data platforms, streaming, data governance, and DevOps, Google Cloud, BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Composer, Dataplex, Vertex AI, and Gemini". This seems like a summary of skills. Could be placed under Skills.
Thus we will have sections: About the role, Responsibilities, Requirements (Required Qualifications), Qualifications (Preferred Qualifications), Skills (technology list). No Benefits, Pay, Schedule as not present.
Now we need to strip boilerplate: The paragraphs about company description, video link, etc. That's "About the company" maybe not needed? The instruction: "Do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short
or drop it." The company description is substantive? It's about Evalueserve. Might be considered background but not required for the role. The instruction says preserve ALL substantive information; does company description count as substantive? It's about the company, not the role. Usually we might keep it under About the role? But the job summary already covers role. The company description could be considered "About the company" but not a heading we have. We could include it as a paragraph under About the role? But the heading "About the role" is for role specifics. However we could treat the initial paragraph after job title as "About the role" includes both role and company? The instruction: "Use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." So we can have About the role section containing role summary and maybe company overview. But we must not invent headings. We'll include company description in About the role as a paragraph. But we must remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. So we need to cut out: - "Watch this video to understand what it means to Elevate Your Impact at Evalueserve!" (maybe keep? It's promotional; could be considered boilerplate? It's not essential to job; but it's part of posting. Might be considered not substantive; but it's about culture. Could keep? Safer to remove as it's not required for role. - "Recognized by Great Place to Work..." etc. That's company culture; could be considered substantive? Might be considered boilerplate but it's about benefits/culture. Since we don't have Benefits section, we could include it under About the role as a paragraph about company culture. However the instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate. This is not EEO; it's about Great Place to Work recognition. Might be okay to keep. - "Please Note : We appreciate the accuracy..." etc. That's application instruction/background verification; should be removed. - "For any assistance, your recruiter is available to support you." removal. - "Want to learn more about our culture and what it’s like to work with us? Write to us at careers@evalueserve.com" removal. - "Follow Us Facebook LinkedIn Instagram Twitter" removal. - "Read our Privacy policy - Evalueserve to learn how Evalueserve processes your personal information." removal. - Disclaimer: "Disclaimer: The following job description serves as an informative reference..." removal. Now we need to preserve all substantive info: job summary, responsibilities, required qualifications, preferred qualifications, skills list. Let's extract exact text. Job Summary paragraph: "We are seeking a senior Data Architect with 15-20 years of experience and strong expertise in Databricks, GCP, cloud data platforms, the Hadoop ecosystem, and modern ETL/ELT architecture. The role will define enterprise data strategy, design scalable Lakehouse solutions, lead data modernization initiatives, and enable analytics, AI/ML, and business intelligence use cases. In addition, the role will architect and guide enterprise data, analytics, and AI solutions on Google Cloud Platform (GCP)." Company description paragraph: "Evalueserve is a leading global company that develops innovative and sustainable solutions for a wide range of clients, including more than 30% of the Fortune 500 companies. With presence in more than 45 countries across five continents, we excel in leveraging state-of-the-art technology, domain-specific AI solutions, and deep subject matter expertise to elevate our clients' strategic decision-making and business impact. Our clients include Amazon, Deutsche Bank, Johnson & Johnson, McDonald's, Microsoft, Morgan Stanley, Nestlé, Novo Nordisk, and Procter & Gamble. We have 5,000+ talented professionals operating across 45 countries, including India, China, Chile, Romania, the US, and Canada. Our global network also extends to emerging markets such as Colombia, the Middle East and the rest of Asia-Pacific. Recognized by Great Place to Work in India, Chile, Romania, the US, and the UK, we offer a dynamic, growth-oriented, and open culture that prioritizes flexible work-life balance, diverse and inclusive teams, and equal opportunities for all." We could include that as part of About the role. Now Responsibilities list: we need to capture each bullet exactly as in posting. Let's copy them: - Design and drive enterprise-scale data architecture using Databricks Lakehouse, Apache Spark, Delta Lake, and cloud-native data platforms. - Lead data platform modernization from legacy Hadoop/data warehouse environments to modern Lakehouse and cloud architecture. - Defining architecture standards for data ingestion, ETL/ELT, data modeling, data warehousing, governance, security, and performance optimization. - Build architecture for batch, near real-time, and streaming data pipelines using Spark, Kafka/Event Hubs/Kinesis, Auto Loader, and workflow orchestration tools. - Work with business leaders, product teams, data engineers, platform teams, and analytics teams to translate business needs into scalable technical solutions. - Guide teams on data quality, metadata management, data lineage, cost optimization, observability, CI/CD, and production support best practices. - Provide technical leadership, review solution designs, mentor engineering teams, and support pre-sales or stakeholder discussions where required. - Serve as a trusted technical advisor to clients on data strategy, architecture,