Machine Learning Engineer

CORE RESPONSIBILITIES

• Create and manage cloud resources in AWS 
• Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies 
• Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform 
• Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations 
• Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
• Define process improvement opportunities to optimize data collection, insights and displays.
• Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible 
• Identify and interpret trends and patterns from complex data sets 
• Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders. 
• Key participant in regular Scrum ceremonies with the agile teams  
• Proficient at developing queries, writing reports and presenting findings 
• Mentor junior members and bring best industry practices 

QUALIFICATIONS

• 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales) 
• Strong background in math, statistics, computer science, data science or related discipline
• Advanced knowledge one of language: Java, Scala, Python, C# 
• Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake  
• Proficient with
• Data mining/programming tools (e.g. SAS, SQL, R, Python)
• Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
• Data visualization (e.g. Tableau, Looker, MicroStrategy)
• Comfortable learning about and deploying new technologies and tools. 
• Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines. 
• Good written and oral communication skills and ability to present results to non-technical audiences 
• Knowledge of business intelligence and analytical tools, technologies and techniques.

Mandatory Requirements 

• Experience in AWS Glue
• Experience in Apache Parquet 
• Proficient in AWS S3 and data lake 
• Knowledge of Snowflake
• Understanding of file-based ingestion best practices.
• Scripting language - Python & pyspark

Requirements:

• 2+ years of experience (4+ for Senior Data Engineer) with system/data integration, development or implementation of enterprise and/or cloud software Engineering degree in Computer Science, Engineering or related field.
• Extensive hands-on experience with data integration/EAI technologies (File, API, Queues, Streams), ETL Tools and building custom data pipelines.
• Demonstrated proficiency with Python, JavaScript and/or Java
• Familiarity with version control/SCM is a must (experience with git is a plus).
• Experience with relational and NoSQL databases (any vendor) Solid understanding of cloud computing concepts.
• Strong organisational and troubleshooting skills with attention to detail.
• Strong analytical ability, judgment and problem-solving techniques Interpersonal and communication skills with the ability to work effectively in a cross functional team.

What you need to have:

• Minimum 1 years of relevant experience, in PySpark (mandatory)
• Hands on experience in development, test, deploy, maintain and improving data integration pipeline in AWS cloud environment is added plus 
• Ability to play lead role and independently manage 3-5 member of Pyspark development team 
• EMR ,Python and PYspark mandate.
• Knowledge and awareness working with AWS Cloud technologies like Apache Spark, , Glue, Kafka, Kinesis, and Lambda in S3, Redshift, RDS

Responsibilities

• Design and implement Azure BI infrastructure, ensure overall quality of delivered solution 
• Develop analytical & reporting tools, promote and drive adoption of developed BI solutions 
• Actively participate in BI community 
• Establish and enforce technical standards and documentation 
• Participate in daily scrums  
• Record progress daily in assigned Devops items 

Ideal Candidates should have

• 5 + years of experience in a similar senior business intelligence development position 
• To be successful in the role you will require a high level of expertise across all facets of the Microsoft BI stack and prior experience in designing and developing well-performing data warehouse solutions 
• Demonstrated experience using development tools such as Azure SQL database, Azure Data Factory, Azure Data Lake, Azure Synapse, and Azure DevOps. 
• Experience with development methodologies including Agile, DevOps, and CICD patterns 
• Strong oral and written communication skills in English 
• Ability and willingness to learn quickly and continuously 
• Bachelor's Degree in computer science 

Key deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.

What will you do?

• You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
• You will be constantly assessing and improving the model using techniques like Transfer learning
• You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
• You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
• Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
• Building predictive models and machine-learning algorithms to apply to data sets.
• Coordinate with different functional teams to implement models and monitor outcomes.
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• Presenting information using data visualization techniques and proposing solutions and strategies to business challenges

We would love to hear from you if :

• You have 2+ years of experience as a software engineer at a SaaS or technology company
• Demonstrable hands-on programming experience with Python/R Data Science Stack
• Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
• Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
• Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
• Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
• Preferable Experience Experienced in web crawling and data scraping
• Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
• Experience with text mining, pattern matching and fuzzy matching

• Brand new Macbook
• Stock Options
• Health Insurance
• Unlimited Sick Leaves
• Passion Fund (Invest in yourself or your passion project)
• Wind Down

Datametica is Hiring for Datastage Developer

• Must have 3 to 8 years of experience in ETL Design and Development using IBM Datastage Components.
• Should have extensive knowledge in Unix shell scripting.
• Understanding of DW principles (Fact, Dimension tables, Dimensional Modelling and Data warehousing concepts).
• Research, development, document and modification of ETL processes as per data architecture and modeling requirements.
• Ensure appropriate documentation for all new development and modifications of the ETL processes and jobs.
• Should be good in writing complex SQL queries.

About Us!

A global Leader in the Data Warehouse Migration and Modernization to the Cloud, we empower businesses by migrating their Data/Workload/ETL/Analytics to the Cloud by leveraging Automation.

We have expertise in transforming legacy Teradata, Oracle, Hadoop, Netezza, Vertica, Greenplum along with ETLs like Informatica, Datastage, AbInitio & others, to cloud-based data warehousing with other capabilities in data engineering, advanced analytics solutions, data management, data lake and cloud optimization.

Datametica is a key partner of the major cloud service providers - Google, Microsoft, Amazon, Snowflake.

We have our own products!

Eagle – Data warehouse Assessment & Migration Planning Product

Raven – Automated Workload Conversion Product

Pelican - Automated Data Validation Product, which helps automate and accelerate data migration to the cloud.

Why join us!

Datametica is a place to innovate, bring new ideas to live and learn new things. We believe in building a culture of innovation, growth and belonging. Our people and their dedication over these years are the key factors in achieving our success.

Benefits we Provide!

Working with Highly Technical and Passionate, mission-driven people

Subsidized Meals & Snacks

Flexible Schedule

Approachable leadership

Access to various learning tools and programs

Pet Friendly

Certification Reimbursement Policy

Check out more about us on our website below!

www.datametica.com

What you need to have: