Snowflake Developer

We are looking for a dynamic Data Engineer to join our team of technology enthusiasts. You will leverage data to drive strategic decision-making and pioneering solutions, working with complex datasets, collaborating closely with stakeholders, and transforming data into actionable insights to drive innovation.

Qualifications and Skills:

• Minimum 4 years of experience as a Data Engineer
• Hands-on experience with Azure cloud-based data solutions
• Fabric experience is a must – designing, implementing, and managing data workflows and pipelines
• Expertise in database design and management, including SQL databases such as SQL Server
• Proficient in ETL (Extract, Transform, Load) design for data integration and processing
• Strong knowledge of data modeling principles and techniques
• Experience with Azure Data Factory (ADF) for orchestrating data workflows
• Ability to analyze and translate data into actionable insights, reports, and visualizations
• Proficiency in Power BI for reporting and data visualization
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Desirable Skills:

• Experience with Power BI Report Builder / Reporting Services
• Knowledge of statistical analysis or Data Science
• Experience within the UK Insurance industry is a plus
• Python or R coding skills

Responsibilities:

• Implement efficient data exchange between internal and external systems to increase efficiency and reduce re-keying and translation errors
• Support the Broking business by developing high-quality information resources, ensuring data availability and accessibility for decision-making
• Engineer data inputs and outputs from core applications and semi-structured remote service data through data syncs between data lake, ODS (SQL database), and leveraging Fabric and ADF
• Perform data engineering tasks including ingestion, cleansing, and collation from a wide range of internal and external sources
• Implement different methods of streaming data and create reconciliations for datasets
• Build analytical models to support reporting and analytics
• Collaborate with an agile delivery team to work on the backlog of specified work

Roles & Responsibilities

• Design, develop, and deliver scalable end-to-end data pipelines using Azure Data Factory, ensuring robust integration

of enterprise-wide data from diverse sources

• Build and optimize data engineering workflows using Databricks and PySpark

• Write efficient, high-performance SQL for data transformation and analysis

• Work with the Azure Cloud platform and associated services, applying strong understanding of data warehousing,

data models, and pipelines

• Provide technical leadership to a team of developers, including code reviews and enforcing best practices across the

development lifecycle

• Oversee CI/CD implementation using Azure DevOps, managing deployments across development, QA, and production

environments with proper change control processes

• Collaborate with cross-functional teams to translate business requirements into scalable data solutions

• Ensure data quality, reliability, and performance across all pipelines and platforms

Ideal Candidate

1Strong Azure Databricks Engineer / Senior Data Engineer Profile

2Mandatory (Experience 1) – Must have minimum 8+ years of overall experience in Data Engineering, Data Development, or related data technology roles, with strong hands-on experience in enterprise data pipeline development.

3Mandatory (Experience 2) – Must have strong hands-on experience with Azure Databricks, including development and optimization of scalable data engineering workflows using Databricks and PySpark.

4Mandatory (Experience 3) – Must have strong hands-on proficiency in PySpark/Python and SQL, with proven experience developing complex data transformations, processing workflows, and performance-optimized queries.

5Mandatory (Experience 4) – Must have hands-on experience with Azure Data Factory (ADF) for designing, developing, and orchestrating end-to-end data pipelines and integrating data from multiple sources.

6Mandatory (Experience 5) – Must have strong experience working on the Azure Cloud platform and associated data services, with solid understanding of data warehousing, data modeling, pipeline architecture, and enterprise data solutions.

7Mandatory (Experience 6) – Must have hands-on experience implementing CI/CD using Azure DevOps, including deployment and release management across development, QA, and production environments.

8Mandatory (Experience 7) – Must have proven technical leadership experience, including code reviews, enforcing development best practices, mentoring developers, and providing technical guidance to a data engineering team.

9Mandatory (Notice Period) – Immediate joiners or candidates who can join within 15 days.

10Mandatory (Note) - The position is open across all Cognizant offices pan India. Candidates must be willing to attend the F2F interview at the nearest Cognizant office location.

We are looking for a Data Engineer with at least 1 year of hands-on experience building solutions on Snowflake. The candidate should be comfortable designing, building, and managing reliable data pipelines that move data from multiple sources into a central data platform.

Responsibilities

• Build and maintain data pipelines for ingesting, transforming, and loading data into Snowflake
• Design scalable data models, schemas, tables, and views in Snowflake
• Develop ETL/ELT workflows using SQL, Python, or data orchestration tools
• Integrate data from APIs, databases, files, and third-party platforms
• Monitor pipeline performance, failures, data quality, and freshness
• Optimize Snowflake queries, warehouses, storage, and compute usage
• Implement incremental loads, change data capture, and scheduled workflows
• Work with engineering and business teams to understand data requirements
• Maintain documentation for pipelines, datasets, and data transformations

Requirements

• 1+ year of hands-on experience working with Snowflake
• Strong SQL skills and experience writing complex queries
• Experience building and managing ETL or ELT data pipelines
• Knowledge of data warehousing concepts, dimensional modelling, and data quality
• Experience with Python or another scripting language
• Familiarity with orchestration tools such as Airflow, Dagster, Prefect, dbt, or similar
• Understanding of APIs, relational databases, file formats, and cloud storage
• Ability to troubleshoot pipeline failures and performance issues
• Strong analytical, problem-solving, and communication skills

Good to Have

• Experience with dbt and Snowflake Tasks, Streams, Snowpipe, or Dynamic Tables
• Knowledge of AWS, Azure, or Google Cloud
• Experience with Kafka or other streaming platforms
• Familiarity with CI/CD, Git, monitoring, and data governance practices
• Experience integrating ERP, finance, or operational systems

At Mitratech, we are a team of technocrats focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available.

For over 35 years, the experts at Mitratech have been focused on solving the complex needs. Today, we serve 20,000 client companies of all sizes globally, representing 30% of the Fortune 500 and over 500,000 users in over 160 countries.

As we continue to grow, we’re always looking for resourceful, enthusiastic, and fresh perspectives. Join our global team and see what makes Mitratech a truly exceptional place to work!

Job Overview 

Principal Data Engineer

About Engineering at Mitratech Legal Solutions 

Mitratech's engineering organization is a collaborative and dynamic environment where engineers are empowered to drive technical direction and innovation. Our engineers are passionate about delivering high-quality products and solutions that meet the evolving needs of our customers, and we're committed to fostering a culture of continuous learning and growth. 

About the Role 

Mitratech is a fast-paced and dynamic environment, and this role requires someone who is adaptable, resilient, and able to thrive in a rapidly changing landscape. If you’re a seasoned engineer with a passion for technical leadership, innovation, and collaboration — including building the data foundations that power trusted reporting and agentic AI-driven products — we’d love to hear from you. 

What You Will Do

•  Drive technical direction for a significant product domain or platform capability, ensuring alignment with business objectives and customer needs 

•  Design and maintain data pipelines and reporting models that power trusted business metrics and increasingly feed agentic AI systems (e.g., RAG ingestion, embeddings, vector stores, AI agent workflows) 

•  Use AI-assisted and agentic engineering tools (e.g., Claude Code, Copilot, Cursor, AI agents) as part of your own workflow, and help other engineers adopt agentic development practices effectively 

•  Reduce systemic complexity by identifying and leading architectural debt remediation, and developing strategies for ongoing technical debt management 

•  Partner with Product and Engineering leadership to inform multi-quarter roadmap feasibility, and provide technical guidance and oversight to ensure successful implementation 

•  Elevate engineering craft across multiple teams through RFCs, mentorship, and knowledge sharing, and develop training programs to improve engineering skills and knowledge 

•  Represent Mitratech’s technical capabilities externally, including speaking at conferences, contributing to open-source projects, and engaging with industry peers and thought leaders 

What We Are Looking For 

To be successful in this role, you will need: 

•  10+ years of experience in software engineering, with a focus on technical leadership and architecture 

•  Deep understanding of data engineering principles, including data modeling, data warehousing, reporting, and data governance 

•  Strong technical expertise in SQL, PostgreSQL, ETL/ELT pipelines, BI tools, and analytics platforms 

•  Practical experience with AI/LLM-adjacent and agentic AI data work — e.g., RAG ingestion pipelines, embedding generation, vector store management, or building/operating AI agent workflows over data — using AI coding assistants (Claude Code, Copilot, Cursor, or similar) as a regular part of the engineering workflow 

•  Working knowledge of modern cloud platforms such as AWS 

•  Experience with BI, reporting, dashboards, and customer-facing analytics 

•  Experience leading cross-functional initiatives with product, engineering, analytics, and business teams 

Nice to Have 

•  Working knowledge of Ruby on Rails and React 

•  Experience with a semantic or metrics layer (e.g., dbt Semantic Layer, headless BI) 

•  Understanding of CI/CD, Git-based workflows, and infrastructure-as-code 

The Stack Context 

•  Modern data stack: Fivetran, Airbyte, dbt, Snowflake, GitHub, Terraform, or similar tools 

•  Application context (nice to have): Ruby on Rails, React, or similar backend/frontend frameworks 

•  Data modeling: SQL, analytics models, documentation, testing, naming standards, and version control 

•  Infrastructure: cloud-based data infrastructure, infrastructure-as-code, CI/CD, monitoring, and cloud storage 

•  Data workflows: ingestion, transformation, orchestration, reporting, deployment, and change management 

•  Reporting focus: trusted metrics, scalable reporting models, dashboards, exports, and data quality 

•  AI surface: data pipelines and quality practices supporting AI/LLM and agentic AI use cases (RAG, embeddings, vector stores, AI agents) alongside traditional BI 

Why This Role 

This role offers a unique opportunity to drive technical direction and innovation at a rapidly growing company, while also mentoring and coaching engineers to improve their craft. As a Principal Data Engineer at Mitratech, you will have the chance to work on complex and challenging problems spanning trusted reporting and agentic AI systems, collaborate with cross-functional teams, and represent the company's technical capabilities externally. If you're looking for a role that offers a mix of technical leadership, data and reporting depth, agentic AI innovation, and collaboration, this could be the perfect fit for you. 

We are an equal-opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability, or veteran status.

About Us

We believe the future of software development is AI-native — where engineers operate at a higher level of abstraction and quality remains non-negotiable. 

Incubyte is a software craft consultancy where the “how” of building software matters as much as the “what”.  

We partner with companies of all sizes, from helping enterprises build, scale, and modernize to early-stage founders bring their ideas to life. 

Our engineers operate in an AI-native development model, using AI as a collaborator across the SDLC to accelerate development while upholding the discipline of software craftsmanship. Guided by Software Craftsmanship and Extreme Programming practices, we build reliable, maintainable, and scalable systems with speed, without compromising quality. If this way of building software resonates with you, we’d like to talk. 

Our Guiding Principles 

These principles define how we work at Incubyte. They are non-negotiable. 

Relentless Pursuit of Quality with Pragmatism 

  We build high-quality systems without losing sight of delivery. 

Extreme Ownership 

  We take responsibility end-to-end for decisions, execution, and outcomes. 

Proactive Collaboration 

  We collaborate closely, challenge each other, and solve problems together. 

Active Pursuit of Mastery 

  We continuously improve our craft and raise our bar. 

Invite, Give, and Act on Feedback 

We seek, give, and act on feedback to get better every day. 

Ensuring Client Success 

We act as trusted partners and focus on real outcomes, not just output. 

Job Description

This is a remote position.

Experience Level

2+ years of experience in SQL, Python, and Snowflake (or equivalent cloud data warehouse), Azure Cloud services.

Role Overview

If you're a Data Craftsperson who takes pride in clean, well-tested data solutions and believes in the principles of Extreme Programming, we'd love to meet you. At Incubyte, we're a DevOps organization where developers own the entire release cycle — you'll get hands-on experience across data engineering, analytics, cloud infrastructure, and direct client communication. This role sits primarily in data engineering (80%) with a meaningful analytics component (20%), supporting our client's data systems end-to-end.

What You'll Do

• Design, build, and maintain data pipelines and infrastructure using SQL and Python
• Work within Snowflake to build and optimize data models supporting business use cases
• Parse and process structured and semi-structured data (JSON, XML) from varied sources
• Diagnose issues across raw, intermediate, and summary tables
• Build SQL queries to support repeatable analytics use cases based on stakeholder requirements
• Investigate and resolve data quality issues, including time-sensitive or urgent ones
• Identify opportunities to consolidate models and maintain a single source of truth (SSOT)

Requirements

What We're Looking For

• 2+ years of experience with SQL and relational databases, with the ability to understand complex data relationships and transformations (required)
• 2+ years of experience with Python for data engineering tasks (required)
• Experience with Snowflake or an equivalent cloud data warehouse (required)
• Experience parsing JSON and XML data (a plus)
• A strong eye for data quality and attention to detail
• Knowledge of Git (required)
• Knowledge of Azure cloud services such as Azure Data Factory, Azure Blob Storage, and Azure SQL Database (required)
• Knowledge of data infrastructure/modeling tools like DBT, Fivetran (a plus)
• Experience with BI tools like Power BI(a plus, not core to this role)
• Knowledge of Docker, Linux, Shell/Bash, and virtualization technologies (a plus)
• Knowledge of SSIS packages (a plus)
• Familiarity with CI/CD methodologies

Benefits

Life at Incubyte  

We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat - with all travel expenses covered. 

Our environment is built for crafters: pairing, refactoring, experimenting with AI, and pushing the boundaries of software excellence. We are all lifelong learners, and our work is our passion. 

Perks

• Dedicated learning & development budget. 
• Sponsorship for conference talks. 
• Comprehensive medical & term insurance.
• Employee-friendly leave policies. 
• Home Office fund 
• Medical Insurance

• Design, build, and maintain scalable ETL/ELT pipelines for batch and real-time data ingestion and transformation.
• Develop and optimize data lake and data warehouse architectures (e.g., Snowflake, BigQuery, Redshift).
• Work with cloud platforms GCP, Azure to manage data infrastructure.
• GCP as mandatory skills
• Collaborate with analytics and product teams to understand data needs and deliver solutions.
• Ensure data quality, reliability, security, and compliance across all data systems.
• Mentor junior data engineers and contribute to best practices and code reviews.
• Monitor and troubleshoot data pipeline performance and resolve data-related issues.
• Automate data validation, monitoring, and alerting processes.
• 8+ years of experience in data engineering or software engineering with a data focus.
• Proficient in SQL and at least one programming language (e.g., Python, Scala, Java).
• Experience with modern data warehousing tools (e.g., Snowflake, Redshift, BigQuery).
• Strong understanding of data modeling, data lakes, and ETL/ELT design.
• Hands-on experience with orchestration tools like Airflow, dbt, or similar.
• Solid experience with cloud data platforms (AWS/GCP/Azure).
• Familiarity with CI/CD pipelines, containerization (Docker/Kubernetes), and version control (Git).
• Experience working in a DevOps or DataOps environment.
• Knowledge of data governance, lineage, and cataloging tools (e.g., Collibra, Alation).
• Familiarity with streaming technologies (Kafka, Spark Streaming, Flink).
• Experience supporting machine learning workflows and data science initiatives.

Job Summary

Role Overview

We are looking for an experienced Data Engineer with strong expertise in Python, ETL, Advanced SQL, CI/CD, DevOps, and Data Analytics. The ideal candidate should have hands-on experience designing and developing scalable data pipelines, transforming large datasets, and supporting data-driven applications.

Experience with Google Cloud Platform (GCP) will be an added advantage.

Key Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python and SQL.
• Develop complex and optimized SQL queries, stored procedures, and data transformations.
• Build and maintain reliable data integration workflows across multiple data sources.
• Perform data cleansing, validation, transformation, and quality checks.
• Analyze data and provide insights to support business and technical requirements.
• Implement and maintain CI/CD pipelines for data engineering applications.
• Work with DevOps practices and tools to automate deployments, monitoring, and infrastructure processes.
• Troubleshoot data pipeline failures, performance issues, and production incidents.
• Optimize data processing workflows for performance, scalability, and reliability.
• Collaborate with Data Analysts, Data Scientists, Developers, and other stakeholders.
• Follow best practices for version control, testing, documentation, and deployment.
• Contribute to cloud-based data engineering initiatives, preferably on GCP.

Required Skills

• 5–7 years of hands-on experience in Data Engineering.
• Strong programming skills in Python.
• Strong expertise in Advanced SQL and database concepts.
• Hands-on experience with ETL/ELT processes and data pipelines.
• Good understanding of Data Warehousing and Data Modeling concepts.
• Experience with CI/CD practices and tools.
• Strong understanding of DevOps principles, automation, and deployment processes.
• Strong data analytics and problem-solving skills.
• Experience working with large datasets and performance optimization.
• Good understanding of Git/version control and software development best practices.

Good to Have

• Hands-on experience with Google Cloud Platform (GCP).
• Exposure to GCP data services such as BigQuery, Cloud Storage, Dataflow, Composer, or Pub/Sub.
• Experience with containerization/orchestration technologies such as Docker/Kubernetes.
• Experience with workflow orchestration tools such as Airflow.
• Knowledge of cloud-based data architecture and distributed data processing.

Preferred Candidate Profile

• Strong analytical and problem-solving abilities.
• Good communication and stakeholder management skills.
• Ability to work independently as well as in a collaborative team environment.
• Strong ownership of data pipelines and production systems.
• Candidates who can join at short notice are preferred.

Mandatory Skills

 Data Engineer, Python , ETL, GCP, Advanced SQL, Strong Data Analytics skills, CICD, Devops

Job Title : Data Engineer – Databricks

Experience : 6+ Years

Location : Noida / Hyderabad / Chennai / Pune / Bengaluru (Hybrid)

Shift : IST (Normal Shift)

Job Summary :

We are seeking an experienced Data Engineer with strong expertise in Databricks, Snowflake, Python, and Spark to build and optimize scalable data pipelines and support AI/ML model deployments. The ideal candidate should have experience working with cloud-based data platforms and preferably possess exposure to the Healthcare domain.

Required Skills :

• Databricks (Preferred)
• Snowflake
• Python
• Apache Spark
• SQL
• Azure Cloud
• Kubernetes
• Apache Airflow
• GitHub & CI/CD Pipelines
• AI/ML Model Deployment
• Data Analytics

Preferred :

• Experience in the Healthcare domain.
• Strong understanding of scalable data engineering architectures and best practices.

Data Engineer – Microsoft Fabric

Location: Pune, India

Work Mode: Hybrid

Experience: 6+ Years

Employment Type: Full-time contactor

Compensation: As per market standards, commensurate with experience and expertise

Shift Timings: 2:00 PM – 11:00 PM IST

Notice Period: 0 – 15 days

About the Role

Jade Business Services (JBS) is seeking a Data Engineer – Microsoft Fabric to join our Pune team and work on enterprise-scale data transformation and analytics initiatives.

We are looking for a hands-on Data Engineer with strong experience in Microsoft Fabric, SQL, Python/PySpark and modern data engineering practices. The candidate will be responsible for building scalable data pipelines, implementing Lakehouse and Warehouse solutions, developing data models and supporting governed, reliable and AI-ready data platforms.

The ideal candidate should be comfortable working with architects, engineering teams and client stakeholders to translate business requirements into scalable and production-ready data solutions.

Roles and Responsibilities

• Design and develop data solutions using Microsoft Fabric, including OneLake, Lakehouse, Warehouse and Data Factory pipelines.
• Build and maintain scalable ETL/ELT pipelines for batch and incremental data processing.
• Develop data ingestion and transformation pipelines using Fabric Data Factory, SQL, Python and/or PySpark.
• Implement Medallion Architecture using Bronze, Silver and Gold layers.
• Work with Lakehouse and Fabric Warehouse for enterprise data processing and analytics.
• Develop and maintain data models, tables, views and optimized SQL queries.
• Build and support semantic models for Power BI and analytical workloads.
• Implement data quality, validation, monitoring and error-handling mechanisms.
• Work with metadata, lineage and governance requirements using Microsoft Purview.
• Implement data security, access controls and role-based permissions across data platforms.
• Support Data Product and domain-oriented data architecture principles.
• Follow DataOps practices including CI/CD, deployment, monitoring and production support.
• Troubleshoot pipeline failures, performance issues and data quality problems.
• Optimize data pipelines, queries and storage for performance and cost efficiency.
• Work closely with Data Architects and business stakeholders to understand requirements and implement technical solutions.
• Participate in technical design discussions, code reviews and architecture reviews.
• Maintain technical documentation, data flow diagrams and pipeline documentation.
• Support production deployments, incident resolution and SLA-driven data platform operations.
• Identify opportunities for automation and AI-assisted improvements across data engineering processes.

Qualifications and Skills

• 6+ years of experience in Data Engineering, Data Integration or Data Platform development.
• Strong hands-on experience with Microsoft Fabric.
• Experience with:
• Microsoft Fabric Lakehouse
• Fabric Warehouse
• OneLake
• Fabric Data Factory / Pipelines
• Semantic Models
• Strong understanding of Lakehouse and Medallion Architecture.
• Strong SQL development and query optimization skills.
• Hands-on experience with Python and/or PySpark.
• Experience developing enterprise ETL/ELT and data integration pipelines.
• Experience with batch and incremental data processing.
• Understanding of data modelling concepts including dimensional modelling.
• Knowledge of data quality, metadata, lineage and data governance.
• Working knowledge of Microsoft Purview.
• Understanding of Data Mesh and Data Product concepts.
• Experience with CI/CD, version control, monitoring and DataOps practices.
• Understanding of cloud security, access controls and data privacy.
• Good troubleshooting and problem-solving skills.
• Strong communication skills and ability to work with distributed and client-facing teams.

Preferred Skills

• Microsoft Fabric or Azure Data certifications.
• Experience migrating workloads from Azure Synapse, SQL Server, Databricks or other data platforms to Microsoft Fabric.
• Experience implementing Medallion Architecture on Microsoft Fabric.
• Experience with Power BI and semantic modelling.
• Exposure to AI/ML, Generative AI or Agentic AI use cases on enterprise data platforms.
• Experience working with Data Products or domain-oriented data solutions.
• Experience in Energy & Utilities, Healthcare, Financial Services or Insurance.
• Experience working with US or international enterprise clients.

What We Expect

The ideal candidate should be hands-on first and capable of independently building, troubleshooting and optimizing Fabric data solutions. You should be able to explain the technical decisions behind your implementation and work effectively with architects and engineering teams to deliver production-ready solutions.

Location: Hyderabad / Chennai

Experience: 5+ years

Employment type: Full-time, permanent

Work Hours: General Shift

website: www.amazech.com

Qualifications: 

• B.E./B.Tech/M.E./M.Tech in Computer Science, Information Technology, Data Science, or related disciplines.
• Strong academic background with relevant industry experience in Data Engineering and Data Warehousing.

Key Responsibilities:

·       Design, develop, and maintain scalable data warehouse solutions using Snowflake.

·       Write, optimize, troubleshoot, and enhance Snowflake SQL queries with a focus on performance and scalability.

·       Develop and support ETL processes using Talend to ensure reliable and efficient data movement.

·       Collaborate with business, analytics, and application teams to enable reporting, dashboards, metrics, and data exploration capabilities.

·       Perform data analysis and resolve issues across data ingestion, transformation, and reporting pipelines.

·       Debug and troubleshoot Python-based data processing scripts and automation workflows.

·       Implement best practices for data quality, testing, deployment, and code reviews.

·       Work across UI, API, and Data Warehouse layers to support end-to-end data integration and business requirements.

·       Monitor, optimize, and maintain data warehouse performance and operational stability.

·       Create and maintain technical documentation, data models, and process workflows.

Required Skills and Experience: 

·       Strong hands-on expertise in Snowflake Data Warehouse.

·       Advanced SQL skills with experience handling large-scale datasets.

·       Strong understanding of Data Warehousing concepts, dimensional modelling, and data architecture.

·       Hands-on experience with Analytical SQL functions, query tuning, and performance optimization.

·       Experience developing and maintaining ETL solutions using Talend.

·       Proficiency in Python for scripting, debugging, automation, and data processing.

·       Experience integrating UI, API, and Data Warehouse workflows.

·       Strong problem-solving and analytical skills.

·       Experience with testing, code reviews, and deployment best practices.

·       Excellent communication and stakeholder management skills.