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As AWS Data Engineer, you are a full-stack data engineer that loves solving business problems. You work with business leads, analysts, and data scientists to understand the business domain and engage with fellow engineers to build data products that empower better decision-making. You are passionate about the data quality of our business metrics and the flexibility of your solution that scales to respond to broader business questions.
If you love to solve problems using your skills, then come join the Team Mactores. We have a casual and fun office environment that actively steers clear of rigid "corporate" culture, focuses on productivity and creativity, and allows you to be part of a world-class team while still being yourself.
What you will do?
- Write efficient code in - PySpark, Amazon Glue
- Write SQL Queries in - Amazon Athena, Amazon Redshift
- Explore new technologies and learn new techniques to solve business problems creatively
- Collaborate with many teams - engineering and business, to build better data products and services
- Deliver the projects along with the team collaboratively and manage updates to customers on time
What are we looking for?
- 1 to 3 years of experience in Apache Spark, PySpark, Amazon Glue
- 2+ years of experience in writing ETL jobs using pySpark, and SparkSQL
- 2+ years of experience in SQL queries and stored procedures
- Have a deep understanding of all the Dataframe API with all the transformation functions supported by Spark 2.7+
You will be preferred if you have
- Prior experience in working on AWS EMR, Apache Airflow
- Certifications AWS Certified Big Data – Specialty OR Cloudera Certified Big Data Engineer OR Hortonworks Certified Big Data Engineer
- Understanding of DataOps Engineering
Life at Mactores
We care about creating a culture that makes a real difference in the lives of every Mactorian. Our 10 Core Leadership Principles that honor Decision-making, Leadership, Collaboration, and Curiosity drive how we work.
1. Be one step ahead
2. Deliver the best
3. Be bold
4. Pay attention to the detail
5. Enjoy the challenge
6. Be curious and take action
7. Take leadership
8. Own it
9. Deliver value
10. Be collaborative
We would like you to read more details about the work culture on https://mactores.com/careers
The Path to Joining the Mactores Team
At Mactores, our recruitment process is structured around three distinct stages:
Pre-Employment Assessment:
You will be invited to participate in a series of pre-employment evaluations to assess your technical proficiency and suitability for the role.
Managerial Interview: The hiring manager will engage with you in multiple discussions, lasting anywhere from 30 minutes to an hour, to assess your technical skills, hands-on experience, leadership potential, and communication abilities.
HR Discussion: During this 30-minute session, you'll have the opportunity to discuss the offer and next steps with a member of the HR team.
At Mactores, we are committed to providing equal opportunities in all of our employment practices, and we do not discriminate based on race, religion, gender, national origin, age, disability, marital status, military status, genetic information, or any other category protected by federal, state, and local laws. This policy extends to all aspects of the employment relationship, including recruitment, compensation, promotions, transfers, disciplinary action, layoff, training, and social and recreational programs. All employment decisions will be made in compliance with these principles.
at Altimetrik
Big Data Engineer: 5+ yrs.
Immediate Joiner
- Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
- Experience in developing lambda functions with AWS Lambda
- Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark
- Should be able to code in Python and Scala.
- Snowflake experience will be a plus
- We can start keeping Hadoop and Hive requirements as good to have or understanding of is enough rather than keeping it as a desirable requirement.
Interfaces with other processes and/or business functions to ensure they can leverage the
benefits provided by the AWS Platform process
Responsible for managing the configuration of all IaaS assets across the platforms
Hands-on python experience
Manages the entire AWS platform(Python, Flask, RESTAPI, serverless framework) and
recommend those that best meet the organization's requirements
Has a good understanding of the various AWS services, particularly: S3, Athena, Python code,
Glue, Lambda, Cloud Formation, and other AWS serverless resources.
AWS Certification is Plus
Knowledge of best practices for IT operations in an always-on, always-available service model
Responsible for the execution of the process controls, ensuring that staff comply with process
and data standards
Qualifications
Bachelor’s degree in Computer Science, Business Information Systems or relevant experience and
accomplishments
3 to 6 years of experience in the IT field
AWS Python developer
AWS, Serverless/Lambda, Middleware.
Strong AWS skills including Data Pipeline, S3, RDS, Redshift with familiarity with other components
like - Lambda, Glue, Step functions, CloudWatch
Must have created REST API with AWS Lambda.
Python relevant exp 3 years
Good to have Experience working on projects and problem solving with large scale multivendor
teams.
Good to have knowledge on Agile Development
Good knowledge on SDLC.
Hands on AWS Databases, (RDS, etc)
Good to have Unit testing exp.
Good to have CICD working knowledge.
Decent communication, as there will be client interaction and documentation.
Education (degree): Bachelor’s degree in Computer Science, Business Information Systems or relevant
experience and accomplishments
Years of Experience: 3-6 years
Technical Skills
Linux/Unix system administration
Continuous Integration/Continuous Delivery tools like Jenkins
Cloud provisioning and management – Azure, AWS, GCP
Ansible, Chef, or Puppet
Python, PowerShell & BASH
Job Details
JOB TITLE/JOB CODE: AWS Python Develop[er, III-Sr. Analyst
RC: TBD
PREFERRED LOCATION: HYDERABAD, IND
POSITION REPORTS TO: Manager USI T&I Cloud Managed Platform
CAREER LEVEL: 3
Work Location:
Hyderabad
Urgent Openings with one of our client
Experience : 3 to 7 Years
Number of Positions : 20
Job Location : Hyderabad
Notice : 30 Days
1. Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
2. Experience in developing lambda functions with AWS Lambda
3. Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark
4. Should be able to code in Python and Scala.
5. Snowflake experience will be a plus
Hadoop and Hive requirements as good to have or understanding of is enough.
WHAT YOU WILL DO:
-
● Create and maintain optimal data pipeline architecture.
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● Assemble large, complex data sets that meet functional / non-functional business requirements.
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● Identify, design, and implement internal process improvements: automating manual processes,
optimizing data delivery, re-designing infrastructure for greater scalability, etc.
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● Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide
variety of data sources using Spark,Hadoop and AWS 'big data' technologies.(EC2, EMR, S3, Athena).
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● Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition,
operational efficiency and other key business performance metrics.
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● Work with stakeholders including the Executive, Product, Data and Design teams to assist with
data-related technical issues and support their data infrastructure needs.
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● Keep our data separated and secure across national boundaries through multiple data centers and AWS
regions.
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● 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.
REQUIRED SKILLS & QUALIFICATIONS:
-
● 5+ years of experience in a Data Engineer role.
-
● Advanced working SQL knowledge and experience working with relational databases, query authoring
(SQL) as well as working familiarity with a variety of databases.
-
● Experience building and optimizing 'big data' data pipelines, architectures and data sets.
-
● Experience performing root cause analysis on internal and external data and processes to answer
specific business questions and identify opportunities for improvement.
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● Strong analytic skills related to working with unstructured datasets.
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● Build processes supporting data transformation, data structures, metadata, dependency and workload
management.
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● A successful history of manipulating, processing and extracting value from large disconnected datasets.
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● Working knowledge of message queuing, stream processing, and highly scalable 'big data' data stores.
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● Strong project management and organizational skills.
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● Experience supporting and working with cross-functional teams in a dynamic environment
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● Experience with big data tools: Hadoop, Spark, Pig, Vetica, etc.
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● Experience with AWS cloud services: EC2, EMR, S3, Athena
-
● Experience with Linux
-
● Experience with object-oriented/object function scripting languages: Python, Java, Shell, Scala, etc.
PREFERRED SKILLS & QUALIFICATIONS:
● Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
Responsibilities: - Write and maintain production level code in Python for deploying machine learning models - Create and maintain deployment pipelines through CI/CD tools (preferribly GitLab CI) - Implement alerts and monitoring for prediction accuracy and data drift detection - Implement automated pipelines for training and replacing models - Work closely with with the data science team to deploy new models to production Required Qualifications: - Degree in Computer Science, Data Science, IT or a related discipline. - 2+ years of experience in software engineering or data engineering. - Programming experience in Python - Experience in data profiling, ETL development, testing and implementation - Experience in deploying machine learning models
Good to have: - Experience in AWS resources for ML and data engineering (SageMaker, Glue, Athena, Redshift, S3) - Experience in deploying TensorFlow models - Experience in deploying and managing ML Flow
They provide both wholesale and retail funding. PM1
- Key responsibility is to design & develop a data pipeline for real-time data integration, processing, executing of the model (if required), and exposing output via MQ / API / No-SQL DB for consumption
- Provide technical expertise to design efficient data ingestion solutions to store & process unstructured data, such as Documents, audio, images, weblogs, etc
- Developing API services to provide data as a service
- Prototyping Solutions for complex data processing problems using AWS cloud-native solutions
- Implementing automated Audit & Quality assurance Checks in Data Pipeline
- Document & maintain data lineage from various sources to enable data governance
- Coordination with BIU, IT, and other stakeholders to provide best-in-class data pipeline solutions, exposing data via APIs, loading in down streams, No-SQL Databases, etc
Skills
- Programming experience using Python & SQL
- Extensive working experience in Data Engineering projects, using AWS Kinesys, AWS S3, DynamoDB, EMR, Lambda, Athena, etc for event processing
- Experience & expertise in implementing complex data pipeline
- Strong Familiarity with AWS Toolset for Storage & Processing. Able to recommend the right tools/solutions available to address specific data processing problems
- Hands-on experience in Unstructured (Audio, Image, Documents, Weblogs, etc) Data processing.
- Good analytical skills with the ability to synthesize data to design and deliver meaningful information
- Know-how on any No-SQL DB (DynamoDB, MongoDB, CosmosDB, etc) will be an advantage.
- Ability to understand business functionality, processes, and flows
- Good combination of technical and interpersonal skills with strong written and verbal communication; detail-oriented with the ability to work independently
Functional knowledge
- Real-time Event Processing
- Data Governance & Quality assurance
- Containerized deployment
- Linux
- Unstructured Data Processing
- AWS Toolsets for Storage & Processing
- Data Security
- We are looking for an experienced data engineer to join our team.
- The preprocessing involves ETL tasks, using pyspark, AWS Glue, staging data in parquet formats on S3, and Athena
To succeed in this data engineering position, you should care about well-documented, testable code and data integrity. We have devops who can help with AWS permissions.
We would like to build up a consistent data lake with staged, ready-to-use data, and to build up various scripts that will serve as blueprints for various additional data ingestion and transforms.
If you enjoy setting up something which many others will rely on, and have the relevant ETL expertise, we’d like to work with you.
Responsibilities
- Analyze and organize raw data
- Build data pipelines
- Prepare data for predictive modeling
- Explore ways to enhance data quality and reliability
- Potentially, collaborate with data scientists to support various experiments
Requirements
- Previous experience as a data engineer with the above technologies
Proficiency in Linux.
Must have SQL knowledge and experience working with relational databases,
query authoring (SQL) as well as familiarity with databases including Mysql,
Mongo, Cassandra, and Athena.
Must have experience with Python/Scala.
Must have experience with Big Data technologies like Apache Spark.
Must have experience with Apache Airflow.
Experience with data pipeline and ETL tools like AWS Glue.
Experience working with AWS cloud services: EC2, S3, RDS, Redshift.
Designation: Specialist - Cloud Service Developer (ABL_SS_600)
Position description:
- The person would be primary responsible for developing solutions using AWS services. Ex: Fargate, Lambda, ECS, ALB, NLB, S3 etc.
- Apply advanced troubleshooting techniques to provide Solutions to issues pertaining to Service Availability, Performance, and Resiliency
- Monitor & Optimize the performance using AWS dashboards and logs
- Partner with Engineering leaders and peers in delivering technology solutions that meet the business requirements
- Work with the cloud team in agile approach and develop cost optimized solutions
Primary Responsibilities:
- Develop solutions using AWS services includiing Fargate, Lambda, ECS, ALB, NLB, S3 etc.
Reporting Team
- Reporting Designation: Head - Big Data Engineering and Cloud Development (ABL_SS_414)
- Reporting Department: Application Development (2487)
Required Skills:
- AWS certification would be preferred
- Good understanding in Monitoring (Cloudwatch, alarms, logs, custom metrics, Trust SNS configuration)
- Good experience with Fargate, Lambda, ECS, ALB, NLB, S3, Glue, Aurora and other AWS services.
- Preferred to have Knowledge on Storage (S3, Life cycle management, Event configuration)
- Good in data structure, programming in (pyspark / python / golang / Scala)