Senior Enterprise Sales /Enterprise Sales-IC

About Blostem:

Blostem is a fintech infrastructure company backed by Rainmatter (Zerodha), MobiKwik, and AC Ventures. We help fintechs embed Fixed Deposits and other financial products in 7 days — vs the traditional 9–12 months.

You'll work on real campaigns, real content, and real pipeline — not just scheduling posts.

What you'll do:

→ B2B content — LinkedIn, email, website

→ Marketing automation and CRM workflows

→ SEO, paid campaign support, and performance reporting

→ Trend-led social content that works for a professional, niche audience

What we're looking for:

We need someone who genuinely lives on the internet.

→ Deep understanding of how LinkedIn, Instagram, and YouTube algorithms work — not surface level

→ Knows what's trending before it peaks — formats, memes, audio, content styles

→ Can spot a good hook, adapt a trend for a B2B/fintech context, and execute fast

→ Understands the difference between content that gets views and content that builds trust

→ Aware of platform-native formats — carousels, short-form video, newsletters, threads

→ Has an eye for what performs in a niche, professional audience vs a mass consumer one

→ Already uses AI tools (ChatGPT, Claude, Perplexity) to research, write, and work faster

→ Writes clearly in English and understands how B2B funnels work

→ Self-starter, fast learner, comfortable in a startup

→ Uses AI for competitor research, content ideation, and summarising long-form material

Director - Data engineering

What are we looking for

real solver?

Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.

Your Responsibilities

what you will wake up to solve.

1. Delivery & Tactical Rigor

• Methodology Implementation: Implement and manage a unified, 'DataOps-First' methodology for data engineering delivery (ETL/ELT pipelines, Data Modeling, MLOps, Data Governance) within assigned business units. This ensures predictable outcomes and trusted data integrity by reducing architecture variability at the project level.
• Operational Stewardship: Drive initiatives to optimize team utilization and enhance operational efficiency within the practice. You manage the commercial success of your squads, ensuring data delivery models (from migration to modern data stack implementation) are executed profitably, scalably, and cost-effectively.
• Execution & Technical Resolution
• Technical Escalation: Serve as the primary escalation point for delivery issues, personally leading the resolution of complex data integration bottlenecks and pipeline failures to protect client timelines and data reliability standards.
• Quality Enforcement
• Quality Oversight: Execute and monitor technical data quality standards, ensuring engineering teams adhere to strict policies regarding data lineage, automated quality checks (observability), security/privacy compliance (GDPR/CCPA/PII), and active catalog management.

2. Strategic Growth & Practice Scaling

• Talent & Scaling Execution: Execute the strategy for data engineering talent acquisition and development within your business units. Implement objective metrics to assess and grow the 'Data-Native' DNA of your teams, ensuring squads are consistently equipped to handle petabyte-scale environments and high-impact delivery.
• Offerings Alignment: Drive the adoption of standardized regional offerings (e.g., Modern Data Platform, Data Mesh, Lakehouse Implementation). Ensure your teams leverage the profitable frameworks defined by the practice to accelerate time-to-insight and eliminate architectural fragmentation in client environments.
• Innovation & IP Development: Lead the practical integration of Vector Databases and LLM-ready architectures into project delivery. Champion the hands-on development of IP and reusable accelerators (e.g., automated ingestion engines) that improve delivery speed and enhance data availability across your portfolio.

3. Leadership & Unit Management

• Unit Leadership: Directly lead, mentor, and manage the Engineering Managers and Lead Architects within your business unit. Hold your teams accountable for project-level operational consistency, technical talent development, and strict adherence to the practice's data governance standards.
• Stakeholder Communication: Clearly articulate the business unit’s operational performance, technical quality metrics, and delivery progress to the C-suite Stakeholders and regional client leadership, bridging the gap between technical execution and business value.
• Ecosystem Alignment: Maintain strong technical relationships with key partner contacts (Snowflake, Databricks, AWS/GCP). Align team delivery capabilities with current product roadmaps and ensure squad-level participation in training, certifications, and partner-led enablement opportunities.

Welcome to Searce

The ‘process-first’, AI-native modern tech consultancy that's rewriting the rules.

We don’t do traditional.

As an engineering-led consultancy, we are dedicated to relentlessly improving the real business outcomes. Our solvers co-innovate with clients to futurify operations and make processes smarter, faster & better.

Functional Skills

1. Delivery Management & Operational Excellence

• Methodology Execution: Expert capability in implementing and enforcing a unified delivery methodology (DataOps, Agile, Mesh Principles) within specific business units. Proven track record of auditing squad-level adherence to ensure consistency across the project lifecycle.
• Operational Performance: High proficiency in managing day-to-day operational metrics, including squad utilization, resource forecasting, and productivity tracking. Skilled at optimizing team performance to meet profitability and efficiency targets.
• SOW & Risk Mitigation: Proven experience in operationalizing Statement of Work (SOW) requirements and identifying technical delivery risks early. Expert at mitigating scope creep and data-specific bottlenecks (e.g., latency, ingestion gaps) before they impact client outcomes.
• Technical Escalation Leadership: Demonstrated ability to lead "war room" efforts to resolve complex pipeline failures or data integrity issues. Skilled at providing clear, rapid remediation plans and communicating technical status directly to regional stakeholders.

2. Architectural Implementation & Technical Oversight

• Modern Stack Proficiency: Deep, hands-on expertise in implementing Cloud-Native architectures (Lakehouse, Data Mesh, MPP) on Snowflake, Databricks, or hyperscalers. Ability to conduct deep-dive architectural reviews and course-correct design decisions at the squad level to ensure scalability.
• Operationalizing Governance: Proven experience in embedding data quality and observability (completeness, freshness, accuracy) directly into the CI/CD pipeline. Responsible for technical enforcement of regulatory compliance (GDPR/PII) and maintaining the integrity of data catalogs across active projects.
• Applied Domain Expertise: Practical experience leading the delivery of high-growth solutions, specifically Generative AI infrastructure (RAG, Vector DBs), Real-Time Streaming, and large-scale platform migrations with a focus on zero-downtime execution.
• DataOps & Engineering Standards: Expert-level mastery of DataOps, including the setup and management of orchestration frameworks (Airflow, Dagster) and Infrastructure as Code (IaC). You ensure that automation is a baseline requirement, not an afterthought, for all delivery teams.

3. Unit Management & Commercial Execution

• Unit & Team Management: Proven success in leading and mentoring Engineering Managers and Lead Architects. Responsible for the operational metrics, technical output, and career development of the business unit's talent pool.
• Offerings Implementation & Scoping: Expertise in translating service offerings (e.g., Data Maturity Assessments, Lakehouse Builds) into accurate project scopes, technical estimates, and resource plans to ensure delivery is both profitable and competitive.
• Talent Growth & Mentorship: Functional ability to implement growth frameworks for data engineering roles. Focus on hands-on coaching and scaling high-performance technical talent to meet the demands of complex, petabyte-scale environments.
• Partner Enablement: Functional competence in managing regional technical relationships with major partners (Snowflake, Databricks, GCP/AWS). Drives squad-level certifications, joint technical enablement, and alignment with partner product roadmaps.

Tech Superpowers

• Modern Data Architect – Reimagines business with the Modern Data Stack (MDS) to deliver data mesh implementations, insights, & real value to clients.
• End-to-End Ecosystem Thinker – Builds modular, reusable data products across ingestion, transformation (ETL/ELT), governance, and consumption layers.
• Distributed Compute Savant – Crafts resilient, high-throughput architectures that survive petabyte-scale volume and data skew without breaking the bank.
• Governance & Integrity Guardian – Embeds data quality, complete lineage, and privacy-by-design (GDPR/PII) into every table, view, and pipeline.
• AI-Ready Orchestrator – Engineers pipelines that bridge structured data with Unstructured/Vector stores, powering RAG models and Generative AI workflows.
• Product-Minded Strategist – Balances architectural purity with time-to-insight; treats every dataset as a measurable "Data Product" with clear ROI.
• Pragmatic Stack Curator – Chooses the simplest tools that compound reliability; fluent in SQL, Python, Spark, dbt, and Cloud Warehouses.
• Builder @ Heart – Writes, reviews, and optimizes queries daily; proves architectures with cost-performance benchmarks, not slideware. Business-first, data-second, outcome focused technology leader.

Experience & Relevance

• Executive Experience: Minimum 10+ years of progressive experience in data engineering and analytics, with at least 3 years in a Senior Manager or Director -level role managing multiple technical teams and owning significant operational and efficiency metrics for a large data service line.
• Delivery Standardization: Demonstrated success in defining and implementing globally consistent, repeatable delivery methodologies (DataOps/Agile Data Warehousing) across diverse teams.
• Architectural Depth: Must retain deep, current expertise in Modern Data Stack architectures (Lakehouse, MPP, Mesh) and maintain the ability to personally validate high-level architectural and data pipeline design decisions.
• Operational Leadership: Proven expertise in managing and scaling large professional services organizations, demonstrated ability to optimize utilization, resource allocation, and operational expense.
• Domain Expertise: Strong background in Enterprise Data Platforms, Applied AI/ML, Generative AI integration, or large-scale Cloud Data Migration.
• Communication: Exceptional executive-level presentation and negotiation skills, particularly in communicating complex operational, data quality, and governance metrics to C-level stakeholders.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

Technical:

• Expertise in WordPress customization, development and knowledge of plugins and API integration Should be well versed in WordPress.
• Must have knowledge to create their own theme and able to do customization in existing/premium theme.
• Must have experience of plugin customization and also aware about a new plugin development.
• Must have the Knowledge of existing WordPress’s functions, hooks, plugins.
• Experience in WordPress is mandatory, other Open Sources/frameworks experience would be considered as an added advantage.
• WordPress integration directly from PSD/AI/Sketch would be considered as an added advantage.
• Must have knowledge of basic php and MYSQL concepts.

Non-Technical:

• Interpersonal skills
• Good communication
• Decision making
• Good Team player
• Good Listener

Roles & Responsibilities:

• Designing and implementing new features and functionality
• Establishing and guiding the website’s architecture
• Ensuring high-performance and availability, and managing all technical aspects of the CMS
• Helping to formulate an effective, responsive design and turning it into a working theme and plugin.

• Developing and maintaining all server-side network components.
• Ensuring optimal performance of the central database and responsiveness to front-end requests.
• Collaborating with front-end developers on the integration of elements.
• Designing customer-facing UI and back-end services for various business processes.
• Developing high-performance applications by writing testable, reusable, and efficient code.
• Implementing effective security protocols, data protection measures, and storage solutions.
• Running diagnostic tests, repairing defects, and providing technical support.
• Documenting Node.js processes, including database schemas, as well as preparing reports.
• Recommending and implementing improvements to processes and technologies.
• Keeping informed of advancements in the field of Node.js development.

1. Data Steward :

Data Steward will collaborate and work closely within the group software engineering and business division. Data Steward has overall accountability for the group's / Divisions overall data and reporting posture by responsibly managing data assets, data lineage, and data access, supporting sound data analysis. This role requires focus on data strategy, execution, and support for projects, programs, application enhancements, and production data fixes. Makes well-thought-out decisions on complex or ambiguous data issues and establishes the data stewardship and information management strategy and direction for the group. Effectively communicates to individuals at various levels of the technical and business communities. This individual will become part of the corporate Data Quality and Data management/entity resolution team supporting various systems across the board.

Primary Responsibilities:

• Responsible for data quality and data accuracy across all group/division delivery initiatives.
• Responsible for data analysis, data profiling, data modeling, and data mapping capabilities.
• Responsible for reviewing and governing data queries and DML.
• Accountable for the assessment, delivery, quality, accuracy, and tracking of any production data fixes.
• Accountable for the performance, quality, and alignment to requirements for all data query design and development.
• Responsible for defining standards and best practices for data analysis, modeling, and queries.
• Responsible for understanding end-to-end data flows and identifying data dependencies in support of delivery, release, and change management.
• Responsible for the development and maintenance of an enterprise data dictionary that is aligned to data assets and the business glossary for the group responsible for the definition and maintenance of the group's data landscape including overlays with the technology landscape, end-to-end data flow/transformations, and data lineage.
• Responsible for rationalizing the group's reporting posture through the definition and maintenance of a reporting strategy and roadmap.
• Partners with the data governance team to ensure data solutions adhere to the organization’s data principles and guidelines.
• Owns group's data assets including reports, data warehouse, etc.
• Understand customer business use cases and be able to translate them to technical specifications and vision on how to implement a solution.
• Accountable for defining the performance tuning needs for all group data assets and managing the implementation of those requirements within the context of group initiatives as well as steady-state production.
• Partners with others in test data management and masking strategies and the creation of a reusable test data repository.
• Responsible for solving data-related issues and communicating resolutions with other solution domains.
• Actively and consistently support all efforts to simplify and enhance the Clinical Trial Predication use cases.
• Apply knowledge in analytic and statistical algorithms to help customers explore methods to improve their business.
• Contribute toward analytical research projects through all stages including concept formulation, determination of appropriate statistical methodology, data manipulation, research evaluation, and final research report.
• Visualize and report data findings creatively in a variety of visual formats that appropriately provide insight to the stakeholders.
• Achieve defined project goals within customer deadlines; proactively communicate status and escalate issues as needed.

Additional Responsibilities:

• Strong understanding of the Software Development Life Cycle (SDLC) with Agile Methodologies
• Knowledge and understanding of industry-standard/best practices requirements gathering methodologies.
• Knowledge and understanding of Information Technology systems and software development.
• Experience with data modeling and test data management tools.
• Experience in the data integration project • Good problem solving & decision-making skills.
• Good communication skills within the team, site, and with the customer

Knowledge, Skills and Abilities

• Technical expertise in data architecture principles and design aspects of various DBMS and reporting concepts.
• Solid understanding of key DBMS platforms like SQL Server, Azure SQL
• Results-oriented, diligent, and works with a sense of urgency. Assertive, responsible for his/her own work (self-directed), have a strong affinity for defining work in deliverables, and be willing to commit to deadlines.
• Experience in MDM tools like MS DQ, SAS DM Studio, Tamr, Profisee, Reltio etc.
• Experience in Report and Dashboard development
• Statistical and Machine Learning models
• Python (sklearn, numpy, pandas, genism)
• Nice to Have:
• 1yr of ETL experience
• Natural Language Processing
• Neural networks and Deep learning
• xperience in keras,tensorflow,spacy, nltk, LightGBM python library

Interaction :  Frequently interacts with subordinate supervisors.

Education : Bachelor’s degree, preferably in Computer Science, B.E or other quantitative field related to the area of assignment. Professional certification related to the area of assignment may be required

Experience :  7 years of Pharmaceutical /Biotech/life sciences experience, 5 years of Clinical Trials experience and knowledge, Excellent Documentation, Communication, and Presentation Skills including PowerPoint

Position: Backend Developer 1 / Backend Engineer:

Location: Bangalore

Experience:  .5 to 4 years, preferably in an agile environment

Strong Knowledge Node.js and MongoDB
Good Knowledge on Flask, SQL and other databases
Good Knowledge on Deployment Process (Nginix, Docker, AWS, Digital Ocean)
Basic Knowledge on Python