Data Engineer

Required Python ,R

work in handling large-scale data engineering pipelines.
Excellent verbal and written communication skills.
Proficient in PowerPoint or other presentation tools.
Ability to work quickly and accurately on multiple projects.

Technical Knowledge (Must Have)

• Strong experience in SQL / HiveQL/ AWS Athena,
• Strong expertise in the development of data pipelines (snaplogic is preferred).
• Design, Development, Deployment and administration of data processing applications.
• Good Exposure towards AWS and Azure Cloud computing environments.
• Knowledge around BigData, AWS Cloud Architecture, Best practices, Securities, Governance, Metadata Management, Data Quality etc.
• Data extraction through various firm sources (RDBMS, Unstructured Data Sources) and load to datalake with all best practices.
• Knowledge in Python
• Good knowledge in NoSQL technologies (Neo4J/ MongoDB)
• Experience/knowledge in SnapLogic (ETL Technologies)
• Working knowledge on Unix (AIX, Linux), shell scripting
• Experience/knowledge in Data Modeling. Database Development
• Experience/knowledge creation of reports and dashboards in Tableau/ PowerBI

Director - Applied AI

Who we are?

Searce is  a niche’ Cloud Consulting business with futuristic tech DNA. We do new-age tech to realise the “Next” in the “Now” for our Clients. We specialise in Cloud Data Engineering, AI/Machine Learning and Advanced Cloud infra tech such as Anthos and Kubernetes. We are one of the top & the fastest growing partners for Google Cloud and AWS globally with over 2,500 clients successfully moved to cloud.

What do we believe?

• Best practices are overrated

• Implementing best practices can only make one an average .

• Honesty and Transparency

• We believe in naked truth. We do what we tell and tell what we do.

• Client Partnership

• Client - Vendor relationship: No. We partner with clients instead. 
• And our sales team comprises 100% of our clients.

How do we work ?

It’s all about being Happier first. And rest follows. Searce work culture is defined by HAPPIER.

• Humble: Happy people don’t carry ego around. We listen to understand; not to respond.

• Adaptable: We are comfortable with uncertainty. And we accept changes well. As that’s what life's about.

• Positive: We are super positive about work & life in general. We love to forget and forgive. We don’t hold grudges. We don’t have time or adequate space for it.

• Passionate: We are as passionate about the great street-food vendor across the street as about Tesla’s new model and so on. Passion is what drives us to work and makes us deliver the quality we deliver.

• Innovative: Innovate or Die. We love to challenge the status quo.

• Experimental: We encourage curiosity & making mistakes.

• Responsible: Driven. Self motivated. Self governing teams. We own it.

So, what are we hunting for ?

1. To devise strategy through the delivery of sustainable intelligent solutions, strategic customer engagements, and research and development
2. To enable and lead our data and analytics team and develop machine learning and AI paths across strategic programs, solution implementation, and customer relationships
3. To manage existing customers and realize new opportunities and capabilities of growth
4. To collaborate with different stakeholders for delivering automated, high availability and secure solutions
5. To develop talent and skills to create a high performance team that delivers superior products
6. To communicate effectively across the organization to ensure that the team is completely aligned to business objectives
7. To build strong interpersonal relationships with peers and other key stakeholders that will contribute to your team's success

Your bucket of Undertakings :

1. Develop an AI roadmap aligned to client needs and vision
2. Develop a Go-To-Market strategy of AI solutions for customers
3. Build a diverse cross-functional team to identify and prioritize key areas of the business across AI, NLP and other cognitive solutions that will drive significant business benefit
4. Lead AI R&D initiatives to include prototypes and minimum viable products
5. Work closely with multiple teams on projects like Visual quality inspection, ML Ops, Conversational banking, Demand forecasting, Anomaly detection etc. 
6. Build reusable and scalable solutions for use across the customer base
7. Create AI white papers and enable strategic partnerships with industry leaders
8. Align, mentor, and manage, team(s) around strategic initiatives
9. Prototype and demonstrate AI related products and solutions for customers
10. Establish processes, operations, measurement, and controls for end-to-end life-cycle management of the digital workforce (intelligent systems)
11. Lead AI tech challenges and proposals with team members
12. Assist business development teams in the expansion and enhancement of a pipeline to support short- and long-range growth plans
13. Identify new business opportunities and prioritize pursuits for AI 

Education & Experience : 

1. Advanced or basic degree (PhD with few years experience, or MS / BS (with many years experience)) in a quantitative field such as CS, EE, Information sciences, Statistics, Mathematics, Economics, Operations Research, or related, with focus on applied and foundational Machine Learning , AI , NLP and/or / data-driven statistical analysis & modelling
2. 10+ years of Experience majorly in applying AI/ML/ NLP / deep learning / data-driven statistical analysis & modelling solutions to multiple domains, including financial engineering, financial processes a plus
3. Strong, proven programming skills and with machine learning and deep learning and Big data frameworks including TensorFlow, Caffe, Spark, Hadoop. Experience with writing complex programs and implementing custom algorithms in these and other environments
4. Experience beyond using open source tools as-is, and writing custom code on top of, or in addition to, existing open source frameworks
5. Proven capability in demonstrating successful advanced technology solutions (either prototypes, POCs, well-cited research publications, and/or products) using ML/AI/NLP/data science in one or more domains
6. Experience in data management, data analytics middleware, platforms and infrastructure, cloud and fog computing is a plus
7. Excellent communication skills (oral and written) to explain complex algorithms, solutions to stakeholders across multiple disciplines, and ability to work in a diverse team

• 1-5 years of experience in building and maintaining robust data pipelines, enriching data, low-latency/highly-performance data analytics applications.
• Experience handling complex, high volume, multi-dimensional data and architecting data products in streaming, serverless, and microservices-based Architecture and platform.
• Experience in Data warehousing, Data modeling, and Data architecture.
• Expert level proficiency with the relational and NoSQL databases.
• Expert level proficiency in Python, and PySpark.
• Familiarity with Big Data technologies and utilities (Spark, Hive, Kafka, Airflow).
• Familiarity with cloud services (preferable AWS)
• Familiarity with MLOps processes such as data labeling, model deployment, data-model feedback loop, data drift.

Key Roles/Responsibilities:

• Act as a technical leader for resolving problems, with both technical and non-technical audiences.
• Identifying and solving issues with data pipelines regarding consistency, integrity, and completeness.
• Lead data initiatives, architecture design discussions, and implementation of next-generation BI solutions.
• Partner with data scientists, tech architects to build advanced, scalable, efficient self-service BI infrastructure.
• Provide thought leadership and mentor data engineers in information presentation and delivery.