Data Delivery Manager is responsible for managing and overseeing the end-to-end delivery of data
solutions, from data architecture and ingestion to processing, analysis, and reporting. This role
ensures that data projects are completed on time, within scope, and aligned with business
objectives. The Data Delivery Manager works with cross-functional teams, including data
engineers, analysts, and other stakeholders, to deliver high-quality data solutions. Key
Responsibilities: Project and Program Management: o Lead and manage the delivery of data-
driven projects, ensuring they are completed on time and within budget. o Develop and maintain
project plans, timelines, and resource allocation. o Monitor project progress and proactively
identify risks, implementing solutions to ensure successful project completion. o Ensure alignment
between data initiatives and business goals, maintaining continuous communication with
stakeholders. Stakeholder Engagement: o Serve as the primary point of contact between business
stakeholders and the data team, translating business requirements into technical specifications. o
Collaborate with business leaders to understand data needs and develop solutions that meet
those needs. o Provide regular updates on project status, risks, and key deliverables to
stakeholders and leadership teams. o Facilitate meetings to gather requirements and
communicate project milestones. Data Strategy & Architecture: o Oversee the design and
implementation of data solutions that support business objectives. o Ensure adherence to data
governance and quality standards throughout the data pipeline lifecycle. o Collaborate with data
architects to define scalable, secure, and high-performance data architectures. o Support data
integration initiatives across different platforms, ensuring smooth and efficient data flow. Team
Leadership and Development: o Manage cross-functional teams of data engineers, analysts, and
other professionals to deliver projects effectively. o Provide leadership and mentoring to team
members, fostering a culture of collaboration, innovation, and continuous learning. o Set clear
expectations, performance goals, and career development opportunities for the team. o Address
and resolve any team challenges, ensuring high levels of productivity and motivation. Quality
Assurance: o Ensure the accuracy, reliability, and quality of data solutions by implementing robust
testing, validation, and review processes. o Develop and enforce data standards, best practices,
and methodologies to ensure consistent, high-quality deliverables. o Drive continuous
improvement initiatives, analyzing past projects and identifying areas for enhancement. Risk
Management and Troubleshooting: o Identify potential risks to project delivery, including data
pipeline issues, resource shortages, or technical blockers, and implement mitigation strategies. o
Troubleshoot and resolve data-related issues and challenges during the project lifecycle.
Reporting and Analytics: o Oversee the creation and maintenance of data dashboards, reports, and
performance metrics. o Ensure that data solutions provide actionable insights for the business,
driving informed decision-making. Experience: o 5+ years of experience in managing programs
related to data management, data engineering, or analytics. o Proven track record in managing
data projects and delivering data solutions in a timely manner. o Experience with data integration,
data warehousing, and data modeling. o Strong understanding of data pipeline management, ETL
processes, and data analytics. Skills: o In-depth knowledge of data management tools and
technologies (e.g., SQL, NoSQL, ETL tools, cloud platforms such as AWS, Google Cloud, or Azure).
o Proficient in project management methodologies (Agile, Scrum, Waterfall). o Strong leadership
and team management skills, with the ability to drive collaboration across different functions. o
Excellent communication skills with the ability to translate complex data-related concepts into
understandable terms for non-technical stakeholders. o Analytical mindset with strong problem-
solving abilities. o Knowledge of data visualization and reporting tools (e.g., Power BI, Tableau,
Looker) is a plus. Certifications: o Project Management Professional (PMP) or Scrum Master
certification (preferred). o Data-related certifications (e.g., AWS Certified Big Data, Google
Professional Data Engineer) are a plus. Preferred Skills: o Experience with big data technologies
(e.g., Hadoop, Spark, Kafka). o Familiarity with machine learning or AI applications related to data
solutions. o Experience with data governance and compliance (e.g., GDPR).
Shubham Vishwakarma
Full Stack Developer - Averlon
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- Collaborate with developers, data scientists, and product managers to implement AI-driven features.
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- Familiarity with Python and ML libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers).
- Basic understanding of LLM concepts such as embeddings, fine-tuning, and inference.
- Knowledge of APIs (OpenAI, Anthropic, Hugging Face, etc.) is a plus.
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- Practical exposure to state-of-the-art AI tools and LLMs.
- Mentorship from AI and software professionals.
- Completion Certificate upon successful completion.
- Letter of Recommendation based on performance.
- Experience to showcase in research projects, academic work, or future AI roles.
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Experience Required: 4 to 5 years in DevOps or related fields
Employment Type: Full-time
About the Role:
We are seeking a highly skilled and experienced Lead DevOps Engineer. This role will focus on driving the design, implementation, and optimization of our CI/CD pipelines, cloud infrastructure, and operational processes. As a Lead DevOps Engineer, you will play a pivotal role in enhancing the scalability, reliability, and security of our systems while mentoring a team of DevOps engineers to achieve operational excellence.
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CI/CD Pipelines: Design and optimize CI/CD pipelines, to improve development velocity and deployment quality.
Automation: Automate repetitive tasks and workflows, such as provisioning cloud resources, configuring servers, managing deployments, and implementing infrastructure as code (IaC) using tools like Terraform, CloudFormation, or Ansible.
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Advanced knowledge of containerization technologies (e.g., Docker, Kubernetes).
Expertise in IaC tools such as Terraform, CloudFormation, or Pulumi.
Hands-on experience with CI/CD tools, particularly Bitbucket Pipelines, Jenkins, GitLab CI/CD, Github Actions or CircleCI.
Proficiency in scripting languages (e.g., Python, Bash, PowerShell).
Soft Skills:
Excellent communication and leadership skills.
Strong analytical and problem-solving abilities.
Proven ability to manage and lead a team effectively.
Experience:
4 years + of experience in DevOps or Site Reliability Engineering (SRE).
4+ years + in a leadership or team lead role, with proven experience managing distributed teams, mentoring team members, and driving cross-functional collaboration.
Strong understanding of microservices, APIs, and serverless architectures.
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Certifications like AWS Certified Solutions Architect, Kubernetes Administrator, or similar.
Experience with GitOps tools such as ArgoCD or Flux.
Knowledge of compliance standards (e.g., GDPR, SOC 2, ISO 27001).
Perks & Benefits:
Competitive salary and performance bonuses.
Comprehensive health insurance for you and your family.
Professional development opportunities and certifications, including sponsored certifications and access to training programs to help you grow your skills and expertise.
Flexible working hours and remote work options.
Collaborative and inclusive work culture.
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PythonParsewave is an SF-based company working closely with frontier AI labs and some of the most sought-after researchers in the field, including Meta and xAI. Our work sits close to model quality, evaluations, benchmark performance, and the technical execution required to help advanced AI teams move quickly and achieve better results.
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Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon