The Data Engineering team is one of the core technology teams of Lumiq.ai and is responsible for creating all the Data related products and platforms which scale for any amount of data, users, and processing. The team also interacts with our customers to work out solutions, create technical architectures and deliver the products and solutions.
If you are someone who is always pondering how to make things better, how technologies can interact, how various tools, technologies, and concepts can help a customer or how a customer can use our products, then Lumiq is the place of opportunities.
Who are you?
- Enthusiast is your middle name. You know what’s new in Big Data technologies and how things are moving
- Apache is your toolbox and you have been a contributor to open source projects or have discussed the problems with the community on several occasions
- You use cloud for more than just provisioning a Virtual Machine
- Vim is friendly to you and you know how to exit Nano
- You check logs before screaming about an error
- You are a solid engineer who writes modular code and commits in GIT
- You are a doer who doesn’t say “no” without first understanding
- You understand the value of documentation of your work
- You are familiar with Machine Learning Ecosystem and how you can help your fellow Data Scientists to explore data and create production-ready ML pipelines
Eligibility
Experience
- At least 2 years of Data Engineering Experience
- Have interacted with Customers
Must Have Skills
- Amazon Web Services (AWS) - EMR, Glue, S3, RDS, EC2, Lambda, SQS, SES
- Apache Spark
- Python
- Scala
- PostgreSQL
- Git
- Linux
Good to have Skills
- Apache NiFi
- Apache Kafka
- Apache Hive
- Docker
- Amazon Certification
Similar jobs
- Bring in industry best practices around creating and maintaining robust data pipelines for complex data projects with/without AI component
- programmatically ingesting data from several static and real-time sources (incl. web scraping)
- rendering results through dynamic interfaces incl. web / mobile / dashboard with the ability to log usage and granular user feedbacks
- performance tuning and optimal implementation of complex Python scripts (using SPARK), SQL (using stored procedures, HIVE), and NoSQL queries in a production environment
- Industrialize ML / DL solutions and deploy and manage production services; proactively handle data issues arising on live apps
- Perform ETL on large and complex datasets for AI applications - work closely with data scientists on performance optimization of large-scale ML/DL model training
- Build data tools to facilitate fast data cleaning and statistical analysis
- Ensure data architecture is secure and compliant
- Resolve issues escalated from Business and Functional areas on data quality, accuracy, and availability
- Work closely with APAC CDO and coordinate with a fully decentralized team across different locations in APAC and global HQ (Paris).
You should be
- Expert in structured and unstructured data in traditional and Big data environments – Oracle / SQLserver, MongoDB, Hive / Pig, BigQuery, and Spark
- Have excellent knowledge of Python programming both in traditional and distributed models (PySpark)
- Expert in shell scripting and writing schedulers
- Hands-on experience with Cloud - deploying complex data solutions in hybrid cloud / on-premise environment both for data extraction/storage and computation
- Hands-on experience in deploying production apps using large volumes of data with state-of-the-art technologies like Dockers, Kubernetes, and Kafka
- Strong knowledge of data security best practices
- 5+ years experience in a data engineering role
- Science / Engineering graduate from a Tier-1 university in the country
- And most importantly, you must be a passionate coder who really cares about building apps that can help people do things better, smarter, and faster even when they sleep
Design, implement, and improve the analytics platform
Implement and simplify self-service data query and analysis capabilities of the BI platform
Develop and improve the current BI architecture, emphasizing data security, data quality
and timeliness, scalability, and extensibility
Deploy and use various big data technologies and run pilots to design low latency
data architectures at scale
Collaborate with business analysts, data scientists, product managers, software development engineers,
and other BI teams to develop, implement, and validate KPIs, statistical analyses, data profiling, prediction,
forecasting, clustering, and machine learning algorithms
Educational
At Ganit we are building an elite team, ergo we are seeking candidates who possess the
following backgrounds:
7+ years relevant experience
Expert level skills writing and optimizing complex SQL
Knowledge of data warehousing concepts
Experience in data mining, profiling, and analysis
Experience with complex data modelling, ETL design, and using large databases
in a business environment
Proficiency with Linux command line and systems administration
Experience with languages like Python/Java/Scala
Experience with Big Data technologies such as Hive/Spark
Proven ability to develop unconventional solutions, sees opportunities to
innovate and leads the way
Good experience of working in cloud platforms like AWS, GCP & Azure. Having worked on
projects involving creation of data lake or data warehouse
Excellent verbal and written communication.
Proven interpersonal skills and ability to convey key insights from complex analyses in
summarized business terms. Ability to effectively communicate with multiple teams
Good to have
AWS/GCP/Azure Data Engineer Certification
Experience: 8+ Years
Work Location: Hyderabad
Mode of work: Work from Office
Senior Data Engineer / Architect
Summary of the Role
The Senior Data Engineer / Architect will be a key role within the data and technology team, responsible for engineering and building data solutions that enable seamless use of data within the organization.
Core Activities
- Work closely with the business teams and business analysts to understand and document data usage requirements
- Develop designs relating to data engineering solutions including data pipelines, ETL, data warehouse, data mart and data lake solutions
- Develop data designs for reporting and other data use requirements
- Develop data governance solutions that provide data governance services including data security, data quality, data lineage etc.
- Lead implementation of data use and data quality solutions
- Provide operational support for users for the implemented data solutions
- Support development of solutions that automate reporting and business intelligence requirements
- Support development of machine learning and AI solution using large scale internal and external datasets
Other activities
- Work on and manage technology projects as and when required
- Provide user and technical training on data solutions
Skills and Experience
- At least 5-8 years of experience in a senior data engineer / architect role
- Strong experience with AWS based data solutions including AWS Redshift, analytics and data governance solutions
- Strong experience with industry standard data governance / data quality solutions
- Strong experience with managing a Postgres SQL data environment
- Background as a software developer working in AWS / Python will be beneficial
- Experience with BI tools like Power BI and Tableau
Strong written and oral communication skills
Requirements-
● B.Tech/Masters in Mathematics, Statistics, Computer Science or another quantitative field
● 2-3+ years of work experience in ML domain ( 2-5 years experience )
● Hands-on coding experience in Python
● Experience in machine learning techniques such as Regression, Classification,Predictive modeling, Clustering, Deep Learning stack, NLP.
● Working knowledge of Tensorflow/PyTorch
Optional Add-ons-
● Experience with distributed computing frameworks: Map/Reduce, Hadoop, Spark etc.
● Experience with databases: MongoDB
The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products.
Responsibilities for Data Engineer
• Create and maintain optimal data pipeline architecture,
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Identify, design, and implement internal process improvements: automating manual processes,
optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Build the infrastructure required for optimal extraction, transformation, and loading of data
from a wide variety of data sources using SQL and AWS big data technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer
acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders including the Executive, Product, Data and Design teams to assist with
data-related technical issues and support their data infrastructure needs.
• Create data tools for analytics and data scientist team members that assist them in building and
optimizing our product into an innovative industry leader.
• Work with data and analytics experts to strive for greater functionality in our data systems.
Qualifications for Data Engineer
• Experience building and optimizing big data ETL pipelines, architectures and data sets.
• Advanced working SQL knowledge and experience working with relational databases, query
authoring (SQL) as well as working familiarity with a variety of databases.
• Experience performing root cause analysis on internal and external data and processes to
answer specific business questions and identify opportunities for improvement.
• Strong analytic skills related to working with unstructured datasets.
• Build processes supporting data transformation, data structures, metadata, dependency and
workload management.
• A successful history of manipulating, processing and extracting value from large disconnected
datasets.
• Experience with Advanced SQL
• Experience with Azure data factory, data bricks,
• Experience with Azure IOT, Cosmos DB, BLOB Storage
• API management, FHIR API development,
• Proficient with Git and CI/CD best practices
• Experience working with Snowflake is a plus
Must Have Skills:
- Solid Knowledge on DWH, ETL and Big Data Concepts
- Excellent SQL Skills (With knowledge of SQL Analytics Functions)
- Working Experience on any ETL tool i.e. SSIS / Informatica
- Working Experience on any Azure or AWS Big Data Tools.
- Experience on Implementing Data Jobs (Batch / Real time Streaming)
- Excellent written and verbal communication skills in English, Self-motivated with strong sense of ownership and Ready to learn new tools and technologies
Preferred Skills:
- Experience on Py-Spark / Spark SQL
- AWS Data Tools (AWS Glue, AWS Athena)
- Azure Data Tools (Azure Databricks, Azure Data Factory)
Other Skills:
- Knowledge about Azure Blob, Azure File Storage, AWS S3, Elastic Search / Redis Search
- Knowledge on domain/function (across pricing, promotions and assortment).
- Implementation Experience on Schema and Data Validator framework (Python / Java / SQL),
- Knowledge on DQS and MDM.
Key Responsibilities:
- Independently work on ETL / DWH / Big data Projects
- Gather and process raw data at scale.
- Design and develop data applications using selected tools and frameworks as required and requested.
- Read, extract, transform, stage and load data to selected tools and frameworks as required and requested.
- Perform tasks such as writing scripts, web scraping, calling APIs, write SQL queries, etc.
- Work closely with the engineering team to integrate your work into our production systems.
- Process unstructured data into a form suitable for analysis.
- Analyse processed data.
- Support business decisions with ad hoc analysis as needed.
- Monitoring data performance and modifying infrastructure as needed.
Responsibility: Smart Resource, having excellent communication skills
- Should have good hands-on experience in Informatica MDM Customer 360, Data Integration(ETL) using PowerCenter, Data Quality.
- Must have strong skills in Data Analysis, Data Mapping for ETL processes, and Data Modeling.
- Experience with the SIF framework including real-time integration
- Should have experience in building C360 Insights using Informatica
- Should have good experience in creating performant design using Mapplets, Mappings, Workflows for Data Quality(cleansing), ETL.
- Should have experience in building different data warehouse architecture like Enterprise,
- Federated, and Multi-Tier architecture.
- Should have experience in configuring Informatica Data Director in reference to the Data
- Governance of users, IT Managers, and Data Stewards.
- Should have good knowledge in developing complex PL/SQL queries.
- Should have working experience on UNIX and shell scripting to run the Informatica workflows and to control the ETL flow.
- Should know about Informatica Server installation and knowledge on the Administration console.
- Working experience with Developer with Administration is added knowledge.
- Working experience in Amazon Web Services (AWS) is an added advantage. Particularly on AWS S3, Data pipeline, Lambda, Kinesis, DynamoDB, and EMR.
- Should be responsible for the creation of automated BI solutions, including requirements, design,development, testing, and deployment
Primary responsibilities:
- Architect, Design and Build high performance Search systems for personalization, optimization, and targeting
- Designing systems with Solr, Akka, Cassandra, Kafka
- Algorithmic development with primary focus Machine Learning
- Working with rapid and innovative development methodologies like: Kanban, Continuous Integration and Daily deployments
- Participation in design and code reviews and recommend improvements
- Unit testing with JUnit, Performance testing and tuning
- Coordination with internal and external teams
- Mentoring junior engineers
- Participate in Product roadmap and Prioritization discussions and decisions
- Evangelize the solution with Professional services and Customer Success teams
- Must have 5-8 years of experience in handling data
- Must have the ability to interpret large amounts of data and to multi-task
- Must have strong knowledge of and experience with programming (Python), Linux/Bash scripting, databases(SQL, etc)
- Must have strong analytical and critical thinking to resolve business problems using data and tech
- Must have domain familiarity and interest of – Cloud technologies (GCP/Azure Microsoft/ AWS Amazon), open-source technologies, Enterprise technologies
- Must have the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
- Must have good communication skills
- Working knowledge/exposure to ElasticSearch, PostgreSQL, Athena, PrestoDB, Jupyter Notebook