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Data Engineer - Python, Apache, Spark
Data Engineer - Python, Apache, Spark
Spica Systems's logo

Data Engineer - Python, Apache, Spark

Priyanka Bhattacharya's profile picture
Posted by Priyanka Bhattacharya
3 - 5 yrs
₹7L - ₹12L / yr
Kolkata
Skills
skill iconPython
Apache Spark
We are a Silicon Valley based start-up, established in 2019 and are recognized as experts in building products and providing R&D and Software Development services in wide range of leading-edge technologies such as LTE, 5G, Cloud Services (Public -AWS, AZURE,GCP,Private – Openstack) and Kubernetes. It has a highly scalable and secured 5G Packet Core Network, orchestrated by ML powered Kubernetes platform, which can be deployed in various multi cloud mode along with a test tool.Headquartered in San Jose, California, we have our R&D centre in Sector V, Salt Lake Kolkata.
 

Requirements:

  • Overall 3 to 5 years of experience in designing and implementing complex large scale Software.
  • Good in Python is must.
  • Experience in Apache Spark, Scala, Java and Delta Lake
  • Experience in designing and implementing templated ETL/ELT data pipelines
  • Expert level experience in Data Pipeline Orchestrationusing Apache Airflow for large scale production deployment
  • Experience in visualizing data from various tasks in the data pipeline using Apache Zeppelin/Plotly or any other visualization library.
  • Log management and log monitoring using ELK/Grafana
  • Git Hub Integration

 

Technology Stack: Apache Spark, Apache Airflow, Python, AWS, EC2, S3, Kubernetes, ELK, Grafana , Apache Arrow, Java

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About Spica Systems

Founded :
2019
Type :
Products & Services
Size :
20-100
Stage :
Raised funding

About

Spica Systems is a software company headquartered in San Jose, California with an R&D facility in Kolkata, India. Their mission is to build enterprise-grade 5G Packet Core and other necessary solutions to define a path to 5G for enterprises. They offer...
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Director - Data engineering


What are we looking for

real solver?

Solver? Absolutely. But not the usual kind. We're searching for the architects of the audacious & the pioneers of the possible. If you're the type to dismantle assumptions, re-engineer ‘best practices,’ and build solutions that make the future possible NOW, then you're speaking our language.


Your Responsibilities

what you will wake up to solve.

1. Delivery & Tactical Rigor

  • Methodology Implementation: Implement and manage a unified, 'DataOps-First' methodology for data engineering delivery (ETL/ELT pipelines, Data Modeling, MLOps, Data Governance) within assigned business units. This ensures predictable outcomes and trusted data integrity by reducing architecture variability at the project level.
  • Operational Stewardship: Drive initiatives to optimize team utilization and enhance operational efficiency within the practice. You manage the commercial success of your squads, ensuring data delivery models (from migration to modern data stack implementation) are executed profitably, scalably, and cost-effectively.
  • Execution & Technical Resolution
  • Technical Escalation: Serve as the primary escalation point for delivery issues, personally leading the resolution of complex data integration bottlenecks and pipeline failures to protect client timelines and data reliability standards.
  • Quality Enforcement
  • Quality Oversight: Execute and monitor technical data quality standards, ensuring engineering teams adhere to strict policies regarding data lineage, automated quality checks (observability), security/privacy compliance (GDPR/CCPA/PII), and active catalog management.

2. Strategic Growth & Practice Scaling

  • Talent & Scaling Execution: Execute the strategy for data engineering talent acquisition and development within your business units. Implement objective metrics to assess and grow the 'Data-Native' DNA of your teams, ensuring squads are consistently equipped to handle petabyte-scale environments and high-impact delivery.
  • Offerings Alignment: Drive the adoption of standardized regional offerings (e.g., Modern Data Platform, Data Mesh, Lakehouse Implementation). Ensure your teams leverage the profitable frameworks defined by the practice to accelerate time-to-insight and eliminate architectural fragmentation in client environments.
  • Innovation & IP Development: Lead the practical integration of Vector Databases and LLM-ready architectures into project delivery. Champion the hands-on development of IP and reusable accelerators (e.g., automated ingestion engines) that improve delivery speed and enhance data availability across your portfolio.

3. Leadership & Unit Management

  • Unit Leadership: Directly lead, mentor, and manage the Engineering Managers and Lead Architects within your business unit. Hold your teams accountable for project-level operational consistency, technical talent development, and strict adherence to the practice's data governance standards.
  • Stakeholder Communication: Clearly articulate the business unit’s operational performance, technical quality metrics, and delivery progress to the C-suite Stakeholders and regional client leadership, bridging the gap between technical execution and business value.
  • Ecosystem Alignment: Maintain strong technical relationships with key partner contacts (Snowflake, Databricks, AWS/GCP). Align team delivery capabilities with current product roadmaps and ensure squad-level participation in training, certifications, and partner-led enablement opportunities.


Welcome to Searce

The ‘process-first’, AI-native modern tech consultancy that's rewriting the rules.

We don’t do traditional.

As an engineering-led consultancy, we are dedicated to relentlessly improving the real business outcomes. Our solvers co-innovate with clients to futurify operations and make processes smarter, faster & better.


Functional Skills

1. Delivery Management & Operational Excellence

  • Methodology Execution: Expert capability in implementing and enforcing a unified delivery methodology (DataOps, Agile, Mesh Principles) within specific business units. Proven track record of auditing squad-level adherence to ensure consistency across the project lifecycle.
  • Operational Performance: High proficiency in managing day-to-day operational metrics, including squad utilization, resource forecasting, and productivity tracking. Skilled at optimizing team performance to meet profitability and efficiency targets.
  • SOW & Risk Mitigation: Proven experience in operationalizing Statement of Work (SOW) requirements and identifying technical delivery risks early. Expert at mitigating scope creep and data-specific bottlenecks (e.g., latency, ingestion gaps) before they impact client outcomes.
  • Technical Escalation Leadership: Demonstrated ability to lead "war room" efforts to resolve complex pipeline failures or data integrity issues. Skilled at providing clear, rapid remediation plans and communicating technical status directly to regional stakeholders.

2. Architectural Implementation & Technical Oversight

  • Modern Stack Proficiency: Deep, hands-on expertise in implementing Cloud-Native architectures (Lakehouse, Data Mesh, MPP) on Snowflake, Databricks, or hyperscalers. Ability to conduct deep-dive architectural reviews and course-correct design decisions at the squad level to ensure scalability.
  • Operationalizing Governance: Proven experience in embedding data quality and observability (completeness, freshness, accuracy) directly into the CI/CD pipeline. Responsible for technical enforcement of regulatory compliance (GDPR/PII) and maintaining the integrity of data catalogs across active projects.
  • Applied Domain Expertise: Practical experience leading the delivery of high-growth solutions, specifically Generative AI infrastructure (RAG, Vector DBs), Real-Time Streaming, and large-scale platform migrations with a focus on zero-downtime execution.
  • DataOps & Engineering Standards: Expert-level mastery of DataOps, including the setup and management of orchestration frameworks (Airflow, Dagster) and Infrastructure as Code (IaC). You ensure that automation is a baseline requirement, not an afterthought, for all delivery teams.

3. Unit Management & Commercial Execution

  • Unit & Team Management: Proven success in leading and mentoring Engineering Managers and Lead Architects. Responsible for the operational metrics, technical output, and career development of the business unit's talent pool.
  • Offerings Implementation & Scoping: Expertise in translating service offerings (e.g., Data Maturity Assessments, Lakehouse Builds) into accurate project scopes, technical estimates, and resource plans to ensure delivery is both profitable and competitive.
  • Talent Growth & Mentorship: Functional ability to implement growth frameworks for data engineering roles. Focus on hands-on coaching and scaling high-performance technical talent to meet the demands of complex, petabyte-scale environments.
  • Partner Enablement: Functional competence in managing regional technical relationships with major partners (Snowflake, Databricks, GCP/AWS). Drives squad-level certifications, joint technical enablement, and alignment with partner product roadmaps.

Tech Superpowers

  • Modern Data Architect – Reimagines business with the Modern Data Stack (MDS) to deliver data mesh implementations, insights, & real value to clients.
  • End-to-End Ecosystem Thinker – Builds modular, reusable data products across ingestion, transformation (ETL/ELT), governance, and consumption layers.
  • Distributed Compute Savant – Crafts resilient, high-throughput architectures that survive petabyte-scale volume and data skew without breaking the bank.
  • Governance & Integrity Guardian – Embeds data quality, complete lineage, and privacy-by-design (GDPR/PII) into every table, view, and pipeline.
  • AI-Ready Orchestrator – Engineers pipelines that bridge structured data with Unstructured/Vector stores, powering RAG models and Generative AI workflows.
  • Product-Minded Strategist – Balances architectural purity with time-to-insight; treats every dataset as a measurable "Data Product" with clear ROI.
  • Pragmatic Stack Curator – Chooses the simplest tools that compound reliability; fluent in SQL, Python, Spark, dbt, and Cloud Warehouses.
  • Builder @ Heart – Writes, reviews, and optimizes queries daily; proves architectures with cost-performance benchmarks, not slideware. Business-first, data-second, outcome focused technology leader.

Experience & Relevance

  • Executive Experience: Minimum 10+ years of progressive experience in data engineering and analytics, with at least 3 years in a Senior Manager or Director -level role managing multiple technical teams and owning significant operational and efficiency metrics for a large data service line.
  • Delivery Standardization: Demonstrated success in defining and implementing globally consistent, repeatable delivery methodologies (DataOps/Agile Data Warehousing) across diverse teams.
  • Architectural Depth: Must retain deep, current expertise in Modern Data Stack architectures (Lakehouse, MPP, Mesh) and maintain the ability to personally validate high-level architectural and data pipeline design decisions.
  • Operational Leadership: Proven expertise in managing and scaling large professional services organizations, demonstrated ability to optimize utilization, resource allocation, and operational expense.
  • Domain Expertise: Strong background in Enterprise Data Platforms, Applied AI/ML, Generative AI integration, or large-scale Cloud Data Migration.
  • Communication: Exceptional executive-level presentation and negotiation skills, particularly in communicating complex operational, data quality, and governance metrics to C-level stakeholders.

Join the ‘real solvers’

ready to futurify?

If you are excited by the possibilities of what an AI-native engineering-led, modern tech consultancy can do to futurify businesses, apply here and experience the ‘Art of the possible’. Don’t Just Send a Resume. Send a Statement.

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We at Royal Purandar take pride in developing and delivering a lifestyle for people who want a blend of nature and modern luxury. We don’t just sell lands or construct villas, we create a living environment that co-exists with nature.  



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skill iconAngular (2+)
Building interactive consumer data from multiple systems and RESTfully abstract to the UI through a Node.js backend
Define code architecture decisions to support a high-performance and scalable product with a minimal footprint.
Collaborate well with engineers, researchers, and data implementation specialists to design and create advanced, elegant and efficient systems.
Experience implementing applications using Angular.
Experience creating front end applications using HTML5, Angular
Hands-on experience with JavaScript Development on both client and server-side
Experience with modern frameworks and design patterns

Knowledge of the following will be considered as an advantage:
Consumer Web Development Experience for High-Traffic, Public Facing web applications
Experience with cloud technologies also a plus
Creating secure RESTful-based web services in XML and JSON, Javascript, JQuery
Version control (SVN, Git).
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KOCH Technology Center 
Its a Product Based Client ,
KOCH Technology Center Its a Product Based Client ,
Agency job
via CareerNet by Mukul Patel
Bengaluru (Bangalore)
3 - 7 yrs
₹7L - ₹15L / yr
Business Intelligence (BI)
Data modeling
PowerBI
Microsoft SSRS
Microsoft Business Intelligence (MSBI)
+1 more
Hi All
Greetings from CareerNet Technologies !
 
 Its pleasure talking to you.
Please find below the details:
Please find below the details:
Role: Power BI Developer
Company: KOCH (https://www.kochind.com/" target="_blank">https://www.kochind.com)
Type: Permanent (Direct payroll)
Edu: Any Full time Graduates 
Exp : 4+ Yrs
Job Location:  Kundalahalli,Near Brookefield Hospital, Bangalore -560037
And as discussed, PFA the JDs and company details and it's principles.

Job Description: 

  • 3+ years’ experience developing and implementing enterprise-scale reports and dashboards.

  • Proficiency with MS Power BI / SSRS.

  • Knowledge of logical and physical data modeling concepts (relational and dimensional).

  • Understanding of structured query language (SQL).

Read more
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