System Programming Jobs in Pune

About Amber (https://amberstudent.com)
Long-term accommodation booking platform for students (think booking.com for
student housing). Amber helps 80M students worldwide, find and book full-time accommodations near their universities, without the hassle of negotiation, nonstandardized and cumbersome paperwork, and a broken payment process.

We are the leading student housing platform globally, with 1M+ student housing units listed in 6 countries and across 80 cities.

We are growing rapidly and targeting $400M in annual gross bookings value by 2022.
If you are passionate about making international mobility and living, seamless and accessible, then - Join us in building the future of student housing!
We are amongst the fastest growing companies in Asia-Pacific as per
Financial times https://www.ft.com/high-growth-asia-pacific-ranking-2022 .

• In charge of converting raw data into usable information for analytics and business decision-making
• Setting up accurate data pipelines to structure the Data and optimize the cost
• 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, and 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 technologies.
• Work with stakeholders including the Executive, Product, Analytics and Design teams to assist with data-related technical issues and support their data infrastructure needs.

• Minimum 2 years of previous experience as a data engineer or in a similar role.
• Technical expertise in data models, data mining, and segmentation
• techniques.
• Knowledge and hands-on with of programming languages (e.g. Java, Python
• and Scala)
• Hands-on experience with SQL database design and AWS lambda function.
• Experience with big data tools: Spark, and Kafka.
• Experience with AWS cloud services: Redshift and S3.
• Experience in ETL frameworks like AWS Glue.
• Experience in designing Data warehousing and streaming processes.

• Fast-paced growth (can skip intermediate levels)
• Total freedom and authority (everything under you, just get the job done!)
• Open and Inclusive Environment
• Great Compensation (and ESOPs)

Data Engineers develop modern data architecture approaches to meet key business objectives and provide end-to-end data solutions. You might spend a few weeks with a new client on a deep technical review or a complete organizational review, helping them to understand the potential that data brings to solve their most pressing problems. On other projects, you might be acting as the architect, leading the design of technical solutions, or perhaps overseeing a program inception to build a new product. It could also be a software delivery project where you're equally happy coding and tech-leading the team to implement the solution.

You’ll spend time on the following:

• You will partner with teammates to create complex data processing pipelines in order to solve our clients’ most ambitious challenges
• You will collaborate with Data Scientists in order to design scalable implementations of their models
• You will pair to write clean and iterative code based on TDD
• Leverage various continuous delivery practices to deploy data pipelines
• Advise and educate clients on how to use different distributed storage and computing technologies from the plethora of options available
• Develop modern data architecture approaches to meet key business objectives and provide end-to-end data solutions
• Create data models and speak to the tradeoffs of different modeling approaches

Here’s what we’re looking for:

• You have a good understanding of data modelling and experience with data engineering tools and platforms such as Kafka, Spark, and Hadoop
• You have built large-scale data pipelines and data-centric applications using any of the distributed storage platforms such as HDFS, S3, NoSQL databases (Hbase, Cassandra, etc.) and any of the distributed processing platforms like Hadoop, Spark, Hive, Oozie, and Airflow in a production setting
• Hands on experience in MapR, Cloudera, Hortonworks and/or cloud (AWS EMR, Azure HDInsights, Qubole etc.) based Hadoop distributions
• You are comfortable taking data-driven approaches and applying data security strategy to solve business problems 
• Working with data excites you: you can build and operate data pipelines, and maintain data storage, all within distributed systems
• Strong communication and client-facing skills with the ability to work in a consulting environment

Looking Data Enginner for our Own organization-

Notice Period- 15-30 days
CTC- upto 15 lpa

Preferred Technical Expertise 

1. Expertise in Python programming.
2. Proficient in Pandas/Numpy Libraries. 
3. Experience with Django framework and API Development.
4. Proficient in writing complex queries using SQL
5. Hands on experience with Apache Airflow.
6. Experience with source code versioning tools such as GIT, Bitbucket etc.

 Good to have Skills:

1. Create and maintain Optimal Data Pipeline Architecture
2. Experienced in handling large structured data.
3. Demonstrated ability in solutions covering data ingestion, data cleansing, ETL, Data mart creation and exposing data for consumers.
4. Experience with any cloud platform (GCP is a plus)
5. Experience with JQuery, HTML, Javascript, CSS is a plus.

• Strong Python Coding skills and OOP skills
• Should have worked on Big Data product Architecture
• Should have worked with any one of the SQL-based databases like MySQL, PostgreSQL and any one of
• NoSQL-based databases such as Cassandra, Elasticsearch etc.
• Hands on experience on frameworks like Spark RDD, DataFrame, Dataset
• Experience on development of ETL for data product
• Candidate should have working knowledge on performance optimization, optimal resource utilization, Parallelism and tuning of spark jobs
• Working knowledge on file formats: CSV, JSON, XML, PARQUET, ORC, AVRO
• Good to have working knowledge with any one of the Analytical Databases like Druid, MongoDB, Apache Hive etc.
• Experience to handle real-time data feeds (good to have working knowledge on Apache Kafka or similar tool)

• Python and Scala (Optional), Spark / PySpark, Parallel programming

• Design, create, test, and maintain data pipeline architecture in collaboration with the Data Architect.
• Build the infrastructure required for extraction, transformation, and loading of data from a wide variety of data sources using Java, SQL, and Big Data technologies.
• Support the translation of data needs into technical system requirements. Support in building complex queries required by the product teams.
• Build data pipelines that clean, transform, and aggregate data from disparate sources
• Develop, maintain and optimize ETLs to increase data accuracy, data stability, data availability, and pipeline performance.
• Engage with Product Management and Business to deploy and monitor products/services on cloud platforms.
• Stay up-to-date with advances in data persistence and big data technologies and run pilots to design the data architecture to scale with the increased data sets of consumer experience.
• Handle data integration, consolidation, and reconciliation activities for digital consumer / medical products.

Job Qualifications:

• Bachelor’s or master's degree in Computer Science, Information management, Statistics or related field
• 5+ years of experience in the Consumer or Healthcare industry in an analytical role with a focus on building on data pipelines, querying data, analyzing, and clearly presenting analyses to members of the data science team.
• Technical expertise with data models, data mining.
• Hands-on Knowledge of programming languages in Java, Python, R, and Scala.
• Strong knowledge in Big data tools like the snowflake, AWS Redshift, Hadoop, map-reduce, etc.
• Having knowledge in tools like AWS Glue, S3, AWS EMR, Streaming data pipelines, Kafka/Kinesis is desirable.
• Hands-on knowledge in SQL and No-SQL database design.
• Having knowledge in CI/CD for the building and hosting of the solutions.
• Having AWS certification is an added advantage.
• Having Strong knowledge in visualization tools like Tableau, QlikView is an added advantage
• A team player capable of working and integrating across cross-functional teams for implementing project requirements. Experience in technical requirements gathering and documentation.
• Ability to work effectively and independently in a fast-paced agile environment with tight deadlines
• A flexible, pragmatic, and collaborative team player with the innate ability to engage with data architects, analysts, and scientists

We are looking for a Data Analyst that oversees organisational data analytics. This will require you to design and help implement the data analytics platform that will keep the organisation running. The team will be the go-to for all data needs for the app and we are looking for a self-starter who is hands on and yet able to abstract problems and anticipate data requirements.
This person should be very strong technical data analyst who can design and implement data systems on his own. Along with him, he also needs to be proficient in business reporting and should have keen interest in provided data needed for business.

Tools familiarity:  SQL, Python, Mix panel, Metabase, Google Analytics,  Clever Tap, App Analytics

Responsibilities

• Processes and frameworks for metrics, analytics, experimentation and user insights, lead the data analytics team
• Metrics alignment across teams to make them actionable and promote accountability
• Data based frameworks for assessing and strengthening Product Market Fit
• Identify viable growth strategies through data and experimentation
• Experimentation for product optimisation and understanding user behaviour
• Structured approach towards deriving user insights, answer questions using data
• This person needs to closely work with Technical and Business teams to get this implemented.

Skills

• 4 to 6 years at a relevant role in data analytics in a Product Oriented company
• Highly organised, technically sound & good at communication
• Ability to handle & build for cross functional data requirements / interactions with teams
• Great with Python, SQL
• Can build, mentor a team
• Knowledge of key business metrics like cohort, engagement cohort, LTV, ROAS, ROE

Eligibility

BTech or MTech in Computer Science/Engineering from a Tier1, Tier2 colleges

Good knowledge on Data Analytics, Data Visualization tools. A formal certification would be added advantage.

We are more interested in what you CAN DO than your location, education, or experience levels.

Send us your code samples / GitHub profile / published articles if applicable.

• Expertise in designing and implementing enterprise scale database (OLTP) and Data warehouse solutions.
• Hands on experience in implementing Azure SQL Database, Azure SQL Date warehouse (Azure Synapse Analytics) and big data processing using Azure Databricks and Azure HD Insight.
• Expert in writing T-SQL programming for complex stored procedures, functions, views and query optimization.
• Should be aware of Database development for both on-premise and SAAS Applications using SQL Server and PostgreSQL.
• Experience in ETL and ELT implementations using Azure Data Factory V2 and SSIS.
• Experience and expertise in building machine learning models using Logistic and linear regression, Decision tree  and Random forest Algorithms.
• PolyBase queries for exporting and importing data into Azure Data Lake.
• Building data models both tabular and multidimensional using SQL Server data tools.
• Writing data preparation, cleaning and processing steps using Python, SCALA, and R.
• Programming experience using python libraries NumPy, Pandas and Matplotlib.
• Implementing NOSQL databases and writing queries using cypher.
• Designing end user visualizations using Power BI, QlikView and Tableau.
• Experience working with all versions of SQL Server 2005/2008/2008R2/2012/2014/2016/2017/2019
• Experience using the expression languages MDX and DAX.
• Experience in migrating on-premise SQL server database to Microsoft Azure.
• Hands on experience in using Azure blob storage, Azure Data Lake Storage Gen1 and Azure Data Lake Storage Gen2.
• Performance tuning complex SQL queries, hands on experience using SQL Extended events.
• Data modeling using Power BI for Adhoc reporting.
• Raw data load automation using T-SQL and SSIS
• Expert in migrating existing on-premise database to SQL Azure.
• Experience in using U-SQL for Azure Data Lake Analytics.
• Hands on experience in generating SSRS reports using MDX.
• Experience in designing predictive models using Python and SQL Server.
• Developing machine learning models using Azure Databricks and SQL Server