Detailed Job Description :-
 Responsible for end to end mapping and quality control of the projects
 Responsible for Design evaluation of mobile phones from standpoint of hardware, schematic and PCB
layout.
 Responsible for database management program for design evaluation from standpoint of HW and MD
design review
 Ensure device quality and manufacturability are built into the development process to ensure good
process robustness from launch by incorporating DFMEA & DFM.
 Conduct internal & external benchmarking of products and implementing QCD ideas.
 Analysis of warranty failures on both process & design level by using SPC & Design guidelines (DFMEA
& DFM) and categorized into SMT process & design failures.
 Project execution from KICK OFF phase to Mass Production by evaluating DFMEA, parts quality &
process validation.
 Develop & execute test plans that address voice of customer (VOC) such as Reliability, Regression &
Functional testing for HW(PCB validation) & Mechanical at both part & product level.
 Estimation of project pricing by bifurcation of key parts PCBA, HW components and mechanical
structure
 Draft documents for process flow, design evaluation - DFMEA, TTM
 Performance evaluation of DUT by Life cycle test, Temperature & humidity mapping, , short circuit
test, breakdown test, cell balancing, BMS parameter verification, self-discharge test, data sheet
verification.
 Validation of HW key parts as Chipset (SoC), DRAM, LCD, TP and Speaker.
 Responsible for planning of complete hardware and reliability testing of handset i.e. current
consumption, basic functioning and battery charging.
 Responsible for benchmark hardware testing and comparison with DUT.
 Responsible for debugging, simulation, and analyzing hardware quality issues.
 Understanding of HW architecture, PCB schematic and layout.
 Review hardware stack for process feasibility and market failure.
 Performing risk assessment to cover all lesson learnt of market issues.
 Understanding of RF instrument functioning & testing of hardware for calls functioning.
 Create detailed, comprehensive and well-structured test plans and test cases.
 Estimate, prioritized, plan and coordinate testing activities.

SSAS

MNC

Agency job

via Fragma Data Systems by Harpreet kour

Bengaluru (Bangalore)

3 - 7 yrs

₹8L - ₹15L / yr

SQL Server Analysis Services (SSAS)

SSAS

Azure Analysis

Azure Analysis Service

SQL

+1 more

1) Experience in developing, optimizing and administering Tabular Models in 'Azure Analysis service' or 'SSAS'.
2) Expertise in developing OLAP cubes and developing complex calculations, Aggregations, implementing a dynamic security model using MDX/ DAX functions in - Azure Analysis service- or (SSAS)
3) Extensively used performance monitor/SQL profiler/DMVs to solve deadlocks, to monitor long-running queries and trouble-shoot cubes SQL and T-SQL. Roles & Responsibilities : 1) "SSAS" OR "Azure Analysis services" Lead Developer with 7+ years of experience in SSAS Azure Data Model Development, SSAS Data model Deployment in Azure, Querying data from SSAS Azure to build Reports.
2) Design and Create SSAS/OLAP/OLTP/Tabular cubes and automate processes for analytical needs.
3) Writing optimized SQL queries for integration with other applications, Maintain data quality and overseeing database security, Partitions and Index.

Data Engineer

at RAPTORX.AI

2 candid answers

Posted by Pratyusha Vemuri

Hyderabad

3 - 6 yrs

₹5L - ₹15L / yr

Fraud

Data Science

Machine Learning (ML)

Data engineers:

Designing and building optimized data pipelines using cutting-edge technologies in a cloud environment to drive analytical insights.This would also include develop and maintain scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity

Constructing infrastructure for efficient ETL processes from various sources and storage systems.

Collaborating closely with Product Managers and Business Managers to design technical solutions aligned with business requirements.

Leading the implementation of algorithms and prototypes to transform raw data into useful information.

Architecting, designing, and maintaining database pipeline architectures, ensuring readiness for AI/ML transformations.

Creating innovative data validation methods and data analysis tools.

Ensuring compliance with data governance and security policies.

Interpreting data trends and patterns to establish operational alerts.

Developing analytical tools, utilities, and reporting mechanisms.

Conducting complex data analysis and presenting results effectively.

Preparing data for prescriptive and predictive modeling.

Continuously exploring opportunities to enhance data quality and reliability.

Applying strong programming and problem-solving skills to develop scalable solutions.

Writes unit/integration tests, contributes towards documentation work

Must have ....

6 to 8 years of hands-on experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed data pipelines.

High proficiency in Scala/Java/ Python API frameworks/ Swagger and Spark for applied large-scale data processing.

Expertise with big data technologies, API development (Flask,,including Spark, Data Lake, Delta Lake, and Hive.

Solid understanding of batch and streaming data processing techniques.

Proficient knowledge of the Data Lifecycle Management process, including data collection, access, use, storage, transfer, and deletion.

Expert-level ability to write complex, optimized SQL queries across extensive data volumes.

Experience with RDBMS and OLAP databases like MySQL, Redshift.

Familiarity with Agile methodologies.

Obsession for service observability, instrumentation, monitoring, and alerting.

Knowledge or experience in architectural best practices for building data pipelines.

Good to Have:

Passion for testing strategy, problem-solving, and continuous learning.

Willingness to acquire new skills and knowledge.

Possess a product/engineering mindset to drive impactful data solutions.

Experience working in distributed environments with teams scattered geographically.