ETL Engineer - Data Pipeline

• 3+ years experience in practical implementation and deployment of ML based systems preferred.
• BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
• Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
• Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
• Experience in working on modeling graph structures related to spatiotemporal systems
• Programming skills in Python
• Experience in developing and deploying on cloud (AWS or Google or Azure)
• Good verbal and written communication skills
• Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow

TOP 3 SKILLS

Python (Language)

Spark Framework

Spark Streaming

Docker/Jenkins/ Spinakar

AWS

Hive Queries

He/She should be good coder.

Preff: - Airflow

Must have experience: -

Python

Spark framework and streaming

exposure to Machine Learning Lifecycle is mandatory.

Project:

This is searching domain project. Any searching activity which is happening on website this team create the model for the same, they create sorting/scored model for any search. This is done by the data

scientist This team is working more on the streaming side of data, the candidate would work extensively on Spark streaming and there will be a lot of work in Machine Learning.

INTERVIEW INFORMATION

3-4 rounds.

1st round based on data engineering batching experience.

2nd round based on data engineering streaming experience.

3rd round based on ML lifecycle (3rd round can be a techno-functional round based on previous

feedbacks otherwise 4th round will be a functional round if required.

Title:  Data Engineer – Snowflake

Location: Mysore (Hybrid model)

Exp-2-8 yrs

Type: Full Time

Walk-in date: 25th Jan 2023 @Mysore 

Job Role: We are looking for an experienced Snowflake developer to join our team as a Data Engineer who will work as part of a team to help design and develop data-driven solutions that deliver insights to the business. The ideal candidate is a data pipeline builder and data wrangler who enjoys building data-driven systems that drive analytical solutions and building them from the ground up. You will be responsible for building and optimizing our data as well as building automated processes for production jobs. You will support our software developers, database architects, data analysts and data scientists on data initiatives

Key Roles & Responsibilities:

• Use advanced complex Snowflake/Python and SQL to extract data from source systems for ingestion into a data pipeline.
• Design, develop and deploy scalable and efficient data pipelines.
• Analyze and assemble large, complex datasets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements. For example: automating manual processes, optimizing data delivery, re-designing data platform infrastructure for greater scalability.
• Build required infrastructure for optimal extraction, loading, and transformation (ELT) of data from various data sources using AWS and Snowflake leveraging Python or SQL technologies.
• Monitor cloud-based systems and components for availability, performance, reliability, security and efficiency
• Create and configure appropriate cloud resources to meet the needs of the end users.
• As needed, document topology, processes, and solution architecture.
• Share your passion for staying on top of tech trends, experimenting with and learning new technologies

Qualifications & Experience

Qualification & Experience Requirements:

• Bachelor's degree in computer science, computer engineering, or a related field.
• 2-8 years of experience working with Snowflake
• 2+ years of experience with the AWS services.
• Candidate should able to write the stored procedure and function in Snowflake.
• At least 2 years’ experience in snowflake developer.
• Strong SQL Knowledge.
• Data injection in snowflake using Snowflake procedure.
• ETL Experience is Must (Could be any tool)
• Candidate should be aware of snowflake architecture.
• Worked on the Migration project
• DW Concept (Optional)
• Experience with cloud data storage and compute components including lambda functions, EC2s, containers.
• Experience with data pipeline and workflow management tools: Airflow, etc.
• Experience cleaning, testing, and evaluating data quality from a wide variety of ingestible data sources
• Experience working with Linux and UNIX environments.
• Experience with profiling data, with and without data definition documentation

• Familiar with Git
• Familiar with issue tracking systems like JIRA (Project Management Tool) or Trello.
• Experience working in an agile environment.

Desired Skills:

• Experience in Snowflake. Must be willing to be Snowflake certified in the first 3 months of employment.
• Experience with a stream-processing system: Snowpipe
• Working knowledge of AWS or Azure
• Experience in migrating from on-prem to cloud systems

Designation: Principal Data Engineer

Experience: Experienced

Position Type: Full Time Position

Location: Hyderabad

Office Timings: 9AM to 6PM

Compensation: As Per Industry standards

About Monarch:

At Monarch, we’re leading the digital transformation of farming. Monarch Tractor augments both muscle and mind with fully loaded hardware, software, and service machinery that will spur future generations of farming technologies. With our farmer-first mentality, we are building a smart tractor that will enhance (not replace) the existing farm ecosystem, alleviate labor availability, and cost issues, and provide an avenue for competitive organic and beyond farming by providing mechanical solutions to replace harmful chemical solutions. Despite all the cutting-edge technology we will incorporate, our tractor will still plow, till, and haul better than any other tractor in its class. We have all the necessary ingredients to develop, build and scale the Monarch Tractor and digitally transform farming around the world.

Description:

Monarch Tractor likes to invite an experience Python data engineer to lead our internal data engineering team in India. This is a unique opportunity to work on computer vision AI data pipelines for electric tractors. You will be dealing with data from a farm environment like videos, images, tractor logs, GPS coordinates and map polygons. You will be responsible for collecting data for research and development. For example, this includes setting up ETL data pipelines to extract data from tractors, loading these data into the cloud and recording AI training results.

This role includes, but not limited to, the following tasks:

● Lead data engineering team

● Own and contribute to more than 50% of the data engineering code base

● Scope out new project requirements

● Costing data pipeline solutions

● Create data engineering tooling

● Design custom data structures for efficient processing of data

Data engineering skills we are looking for:

● Able to work with large amounts of text log data, image data, and video data

● Fluently use AWS cloud solutions like S3, Lambda, and EC2

● Able to work with data from Robot Operating System

Required Experience:

● 3 to 5 years of experience using Python

● 3 to 5 years of experience using PostgreSQL

● 3 to 5 years of experience using AWS EC2, S3, Lambda

● 3 to 5 years of experience using Ubuntu OS or WSL

Good to have experience:

● Ray

● Robot Operating System

What you will get:

At Monarch Tractor, you’ll play a key role on a capable, dedicated, high-performing team of rock stars. Our compensation package includes a competitive salary, excellent health, dental and vision benefits, and company equity commensurate with the role you’ll play in our success. 

• Proficient with SQL Server/T-SQL programming in creation and optimization of complex Stored Procedures, UDF, CTE and Triggers
• Overall Experience should be between 4 to 7 years
• Experience working in a data warehouse environment and a strong understanding of dimensional data modeling concepts. Experience in SQL server, DW principles and SSIS.
• Should have strong experience in building data transformations with SSIS including importing data from files, and moving data from source to destination.
• Creating new SSIS packages or modifying existing SSIS packages using SQL server
• Debug and fine-tune SSIS processes to ensure accurate and efficient movement of data. Experience with ETL testing & data validation.
• 1+ years of experience with Azure services like Azure Data Factory, Data flow, Azure blob Storage, etc.
• 1+ years of experience with developing Azure Data Factory Objects - ADF pipeline, configuration, parameters, variables, Integration services runtime.
• Must be able to build Business Intelligence solutions in a collaborative, agile development environment.
• Reporting experience with Power BI or SSRS is a plus.
• Experience working on an Agile/Scrum team preferred.
• Proven strong problem-solving skills, troubleshooting, and root cause analysis.
• Excellent written and verbal communication skills.

• Collaborate with the business teams to understand the data environment in the organization; develop and lead the Data Scientists team to test and scale new algorithms through pilots and subsequent scaling up of the solutions
• Influence, build and maintain the large-scale data infrastructure required for the AI projects, and integrate with external IT infrastructure/service
• Act as the single point source for all data related queries; strong understanding of internal and external data sources; provide inputs in deciding data-schemas
• Design, develop and maintain the framework for the analytics solutions pipeline
• Provide inputs to the organization’s initiatives on data quality and help implement frameworks and tools for the various related initiatives
• Work in cross-functional teams of software/machine learning engineers, data scientists, product managers, and others to build the AI ecosystem
• Collaborate with the external organizations including vendors, where required, in respect of all data-related queries as well as implementation initiatives